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Hwang, Heungsun 1969. "Structural equation modeling by extended redundancy analysis." Thesis, McGill University, 2000. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=36954.
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A new approach to structural equation modeling based on so-called extended redundancy analysis (ERA) is proposed. In ERA, latent variables are obtained as exact linear combinations of observed variables, and model parameters are estimated by consistently minimizing a single criterion. As a result, the method can avoid limitations of covariance structure analysis (e.g., stringent distributional assumptions, improper solutions, and factor score indeterminacy) in addition to those of partial least squares (e.g., the lack of a global optimization procedure). The method is simple yet versatile enough to fit more complex models; e.g., those with higher-order latent variables and direct effects of observed variables. It can also fit a model to more than one sample simultaneously. Other relevant topics are also discussed, including data transformations, missing data, metric matrices, robust estimation, and efficient estimation. Examples are given to illustrate the proposed method.
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Joshi, Hemanta. "Determinants of mathematics achievement using structural equation modeling." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq23000.pdf.
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Codd, Casey L. "Nonlinear Structural Equation Models: Estimation and Applications." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1301409131.
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Turner, John R. "Knowledge Sharing: Examining Employee Perceptions Using Structural Equation Modeling." Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc804846/.
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During team decision-making practices information is often shared among team members as part of the decision making process. Knowledge sharing involves one team member sharing information so that other team members can encode the knowledge to make their own mental representation of the new information (Huan & Jiang, 2012). Unfortunately, the literature has shown that new information is not always shared between team members during decision making processes (Stasser & Titus, 1985). When teams make decisions without considering all the information available poor decisions can result. This research study tests a team conceptual model derived by Turner (2013) addressing attitudes toward knowledge sharing. Structural equation modeling was conducted to test a portion of Turner’s (2013) team conceptual model. The tested model included the independent variables of psychological safety, team conflict, team cohesion, and transactive memory systems. The dependent variable for the dissertation was knowledge sharing.
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Lortie, Brendan. "A Structural Equation Modeling Approach to Predicting Applicant Faking." Bowling Green State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1573323760174055.
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Pfleger, Phillip Isaac. "Exploring Fit for Nonlinear Structural Equation Models." BYU ScholarsArchive, 2019. https://scholarsarchive.byu.edu/etd/7370.
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Fit indices and fit measures commonly used to determine the accuracy and desirability of structural equation models are expected to be insensitive to nonlinearity in the data. This includes measures as ubiquitous as the CFI, TLI, RMSEA, SRMR, AIC, and BIC. Despite this, some software will report these measures when certain models are used. Consequently, some researchers may be led to use these fit measures without realizing the impropriety of the act. Alternative fit measures have been proposed, but these measures require further testing. As part of this thesis, a large simulation study was carried out to investigate alternative fit measures and to confirm whether the traditional measures are practically blind to nonlinearity in the data. The results of the simulation provide conclusive evidence that fit statistics and fit indices based on the chi-square distribution or the residual covariance matrix are entirely insensitive to nonlinearity. The posterior predictive p-value was also insensitive to nonlinearity. Only fit measures based on the structural residuals (i.e., HFI and R-squared) showed any sensitivity to nonlinearity. Of these, the R-squared was the only reliable measure of nonlinear model misspecification. This thesis shows that an effective strategy for determining whether a nonlinear model is preferable to a linear one involves using the R-squared to compare models that have been fit to the same data. An R-squared that is much larger for the nonlinear model than the linear model suggests that the linear model may be less desirable than the nonlinear model. The proposed method is intended to be supplementary to substantive theory. It is argued that any dependence on fit indices or fit statistics that places these measures on a higher pedestal than substantive theory will invariably lead to blindness on the part of the researcher. In other words, unwavering adherence to goodness-of-fit measures limits the researcher<'>s vision to what the measures themselves can detect.
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Miles, Carol A. "Structural equation modeling of the WISC-III, a developmental approach." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape15/PQDD_0014/NQ31054.pdf.
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Geiser, Christian [Verfasser]. "Structural equation modeling of multitrait-multimethod-multioccasion data / Christian Geiser." Berlin : Freie Universität Berlin, 2008. http://d-nb.info/1023232111/34.
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Zhao, Hongxia. "Examining Contributors to Preschoolers’ Classroom Engagement using Structural Equation Modeling." Digital Commons @ East Tennessee State University, 2018. https://dc.etsu.edu/etd/3475.
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The purpose of this study is to demonstrate whether and how teacher-child interactions, teacher-child relationships, children’s self-control, parents’ education levels, teachers’ teaching experience and education levels, and classroom physical environment impact children’s engagement levels. Preschoolers from Head Start programs and a university childcare center (N = 135, M = 54.93 months, SD = 7.50) and 15 preschool classroom teachers in East Tennessee participated in the study. Classroom head teachers rated child’s engagement, teacher-child interaction, teacher-child relationships, and children’s self-control using provided questionnaires. The primary researcher assessed the classroom physical environment and determined the reliability for the Children’s Physical Environments Rating Scale (CPERS). The structural equation modeling (SEM) statistical approach was employed to analyze the data.
The results showed that the level of preschoolers’ engagement in classroom learning activities was directly associated with their self-control (β = .37, p < .001). Preschoolers’ engagement was not indirectly associated with children’s self-control through teacher-child interaction. The level of engagement of preschoolers in classroom learning activities did not directly associate with teacher-child relationships but was indirectly associated with the teacher-child relationship through children’s self-control (β = .20 , p < .001 ). When separating the two subscales of teacher-child relationship (closeness and conflict), teacher-child closeness was directly associated with children’s engagement level (β = .22, p = .003). In addition, teacher-child conflict was both directly (β = - .17, p = .022) and indirectly associated with child’s engagement level through children’s self-control (β = .26, p < .001). Classroom physical environment did not directly predict the level of engagement of preschoolers, while indirect relationships were found between the classroom physical environment scores and the level of engagement of preschoolers, and the relationship was mediated by children’s self-control (β = .09, p = .050).
The study offers implications for teachers as they work on enhancing children’s engagement level in their learning activities. Future research suggested by this study include further exploration of intervention strategies to increase children’s active engagement. Increasing sample size and obtaining reliability of the measures on children’s behaviors would also improve the rigor of the study.
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Kobayashi, Wakako. "Structural Equation Modeling of Writing Proficiency Using Can-Do Questionnaires." Diss., Temple University Libraries, 2017. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/461909.
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Teaching & Learning<br>Ed.D.<br>The purposes of this study were to validate the writing section of the Eiken Can-Do Questionnaires used in this study and the second purpose was to determine the effects of ten affective orientations (i.e., Desire to Write English, Attitude Toward Learning to Write English, Motivational Intensity, Instrumental Orientation for Writing in English, L2 Writing Anxiety, L2 Writing Self-Confidence, Willingness to Communicate in L2 Writing, Self-Esteem, Cognitive Competence, and General Self-Worth), on the participants’ responses to the Eiken Can-Do Questionnaires. This purpose is valuable because little is known about the relationship between Can-Do Questionnaire and affective variables investigated in this study. The final purpose of this study was to develop Can-Do Questionnaires as an internal measure for a university writing class. The participants of this study were 204 university students studying in two private universities in Tokyo, Japan. The first instrument was the writing section of the Eiken Can-Do Questionnaire; this questionnaire served as the outside measure in this study. The second, six out of nine essays written by the students were assessed as a measure of their writing ability in English. The Affective Orientation Questionnaire was administered to measure ten Affective Orientations. The questionnaire and essay data were analyzed using the Rasch rating scale. All of the participants completed the Background Questionnaire and Affective Orientation Questionnaire in April 2010 and 2011 and completed the writing section of the Eiken Can-do Questionnaire in April, July, and December 2010 and 2011. six writing assignments were produced by 179 out of the 204 participants wrote during the 2010 and 2011 academic year, and the relationships among the variables were analyzed using Structural Equation Modeling. The results indicated that the use of the Eiken Can-Do Questionnaires as the proficiency level measure was appropriate for this group of university students. The Eiken Can-Do Questionnaires were predictors of Motivation and L2 Self-Confidence. Motivation was a predictor of WTC in L2 Writing. Therefore, it should be noted that the Eiken Can-Do Questionnaires had an indirect effect with WTC in L2 Writing. The result implies that through having Eiken Can-Do questionnaires and Classroom Can-do Questionnaires to achieve their future goals, their English classes and their future learning objectives were connected. It is necessary to provide students with adequate practice and guidance in using the Eiken Can-Do Questionnaires in order to promote a deeper understanding of their purposes and uses.<br>Temple University--Theses
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Jaffari, Fathima. "MODEL-FREE MEASUREMENT OF CASE INFLUENCE IN STRUCTURAL EQUATION MODELING." OpenSIUC, 2019. https://opensiuc.lib.siu.edu/dissertations/1689.
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This study introduces a new model-free case influence measure (DOCR) to the SEM field and evaluates its performance compared to that of Mahalanobis Distance (MD) and Generalized Cook’s Distance (gCD) when the sample size, proportion of target cases to non-target cases, and type of model used to generate the data are manipulated. The findings suggest the DOCR measure generally performed better than MD and gCD in identifying the target cases across all simulated conditions. However, the performance of the DOCR measure under small sample size was not satisfactory, and it raised a red flag about the sensitivity of this measure to small sample sizes. Therefore, researchers and practitioners should only use the DOCR measure with sufficiently large sample sizes, but not larger than 600.
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Zahery, Mahsa. "OPTIMIZATION FOR STRUCTURAL EQUATION MODELING: APPLICATIONS TO SUBSTANCE USE DISORDERS." VCU Scholars Compass, 2018. https://scholarscompass.vcu.edu/etd/5261.
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Substance abuse is a serious issue in both modern and traditional societies. Besides health complications such as depression, cancer and HIV, social complications such as loss of concentration, loss of job, and legal problems are among the numerous hazards substance use disorder imposes on societies. Understanding the causes of substance abuse and preventing its negative effects continues to be the focus of much research.
Substance use behaviors, symptoms and signs are usually measured in form of ordinal data, which are often modeled under threshold models in Structural Equation Modeling (SEM). In this dissertation, we have developed a general nonlinear optimizer for the software package OpenMx, which is a SEM package in widespread use in the fields of psychology and genetics. The optimizer solves nonlinearly constrained optimization problems using a Sequential Quadratic Programming (SQP) algorithm. We have tested the performance of our optimizer on ordinal data and compared the results with two other optimizers (implementing SQP algorithm) available in the OpenMx package. While all three optimizers reach the same minimum, our new optimizer is faster than the other two.
We then applied OpenMx with our optimization engine to a very large population-based drug abuse dataset, collected in Sweden from over one million pairs, to investigate the effects of genetic and environmental factors on liability to drug use.
Finally, we investigated the reasons behind better performance of our optimizer by profiling all three optimizers as well as analyzing their memory consumption. We found that objective function evaluation is the most expensive task for all three optimizers, and that our optimizer needs fewer number of calls to this function to find the minimum. In terms of memory consumption, the optimizers use the same amount of memory.
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Aydin, Utkun. "A Structural Equation Modeling Study: The Metacognition-knowledge Model For Geometry." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608523/index.pdf.
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The purpose of this study is twofold: (1) to examine the effects of knowledge on cognition and regulation of cognition on declarative knowledge, conditional knowledge, and procedural knowledge in geometry and (2) to examine the interrelationships among declarative knowledge, conditional knowledge, and procedural knowledge in geometry. The reciprocal relationships between metacognitive and knowledge factors were modeled by using data from tenth grade secondary school students.
Structural equation modeling was used to test the hypothesized relationships of two metacognitive factors (knowledge of cognition, regulation of cognition) and three knowledge factors (declarative knowledge, conditional knowledge, procedural knowledge). The observed variables representing the latent variables were determined by carrying out exploratory factor analysis and confirmatory factor analysis for the metacognitive awareness inventory and geometry knowledge test separately.
Major findings revealed: (1) Declarative knowledge significantly and positively influences conditional and procedural knowledge<br>(2) Procedural knowledge has a signitificant and positive direct effect on conditional knowledge<br>(3) Declarative knowledge has a positive indirect effect on conditional knowledge<br>(4) Knowledge of cognition significantly and positively influences procedural knowledge<br>(5) Regulation of cognition has a significant but negative direct effect on procedural knowledge<br>(6) Knowledge of cognition has positive indirect effects on conditional and procedural knowledge<br>(7) Regulation of cognition has negative indirect effects on conditional and procedural knowledge<br>(8) Knowledge of cognition and regulation of cognition have non-significant direct effect on declarative and conditional knowledge.
The results showed that knowledge of cognition has the strongest direct effect on procedural knowledge and the direct effect of declarative knowledge on conditional knowledge is stronger than on procedural knowledge. In view of the findings considerable suggestions is provided for teachers, instructional designers, and mathematics education researchers.
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Koch, Tobias [Verfasser]. "Multilevel Structural Equation Modeling of Multitrait-Multimethod-Multioccasion Data / Tobias Koch." Berlin : Freie Universität Berlin, 2013. http://d-nb.info/1036872866/34.
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Witherspoon, Ryan G. "Exploring Polyamorous Resilience and Strength Factors| A Structural Equation Modeling Approach." Thesis, Alliant International University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10841959.
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<p> Polyamory is a type of consensual non-monogamy (CNM) in which participants engage in multiple simultaneous romantic and often sexual relationships with the knowledge and consent of all involved. CNM practitioners in general, and polyamorous people in specific, appear to be highly stigmatized due to their relational practices, and to frequently encounter CNM-related discrimination, harassment, and violence (DHV). Conceptualizing this dynamic via minority stress theory predicts that this stigma and DHV will lead to negative mental health outcomes for polyamorous individuals. However, recent research has begun to identify possible sources of resilience and strength within polyamorous populations, which may ameliorate these negative effects, as well as enhance satisfaction with CNM and quality of life. This study investigated these hypotheses in a sample of 1,176 polyamorous American adults utilizing structural equation modeling (SEM). Two structural models were proposed and tested, one for polyamorous resilience and one for polyamorous strengths. Four constructs were assessed as potential resilience and strength factors: mindfulness, cognitive flexibility, a positive CNM identity, and connection to a supportive CNM community. Results indicate that CNM-related minority stress was positively related to increased psychological distress, such as higher self-reported depression and anxiety symptoms. Mindfulness was found to have both direct and moderating effects on the relationship between minority stress and psychological distress, such that higher mindfulness attenuated the negative impact of minority stress. Cognitive flexibility also displayed direct and moderating effects, but in the opposite than predicted direction. Regarding polyamorous strengths, mindfulness was found to positively impact overall satisfaction with CNM as well as life satisfaction. In addition, greater connection to a supportive CNM community correlated with having a more positive sense of CNM identity, which in turn was related to higher satisfaction with CNM. Overall satisfaction with CNM was related to greater life satisfaction. Clinical and research implications of these findings are discussed, with an emphasis on improving cultural competence for clinicians working with this unique and under-served population.</p><p>
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JO, SON MI. "A Study of Korean Students' Creativity in Science Using Structural Equation Modeling." Diss., The University of Arizona, 2009. http://hdl.handle.net/10150/193568.
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Through the review of creativity research I have found that studies lack certain crucial parts: a) a theoretical framework for the study of creativity in science, b) studies considering the unique components related to scientific creativity, and c) studies of the interactions among key components through simultaneous analyses. The primary purpose of this study is to explore the dynamic interactions among four components (scientific proficiency, intrinsic motivation, creative competence, context supporting creativity) related to scientific creativity under the framework of scientific creativity. A total of 295 Korean middle school students participated. Well-known and commonly used measurements were selected and developed. Two scientific achievement scores and one score measured by performance-based assessment were used to measure student scientific knowledge/inquiry skills. Six items selected from the study of Lederman, Abd-El-Khalick, Bell, and Schwartz (2002) were used to assess how well students understand the nature of science. Five items were selected from the subscale of the scientific attitude inventory version II (Moore & Foy, 1997) to assess student attitude toward science. The Test of Creative Thinking-Drawing Production (Urban & Jellen, 1996) was used to measure creative competence. Eight items chosen from the 15 items of the Work Preference Inventory (1994) were applied to measure students' intrinsic motivation. To assess the level of context supporting creativity, eight items were adapted from measurement of the work environment (Amabile, Conti, Coon, Lazenby, and Herron, 1996). To assess scientific creativity, one open-ended science problem was used and three raters rated the level of scientific creativity through the Consensual Assessment Technique (Amabile, 1996). The results show that scientific proficiency and creative competence correlates with scientific creativity. Intrinsic motivation and context components do not predict scientific creativity. The strength of relationships between scientific proficiency and scientific creativity (estimate parameter=0.43) and creative competence and scientific creativity (estimate parameter=0.17) are similar [Δx²(.05)(1)=0.670, P > .05]. In specific analysis of structural model, I found that creative competence and scientific proficiency play a role of partial mediators among three components (general creativity, scientific proficiency, and scientific creativity). The moderate effects of intrinsic motivation and context component were investigated, but the moderation effects were not found.
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Farmer, G. Lawrence. "Using structural equation modeling to asses two theoretical models that explain dropout." FIU Digital Commons, 1996. http://digitalcommons.fiu.edu/etd/3252.
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This study evaluated the relative fit of both Finn's (1989) Participation-Identification and Wehlage, Rutter, Smith, Lesko and Fernandez's (1989) School Membership models of high school completion to a sample of 4,597 eighth graders taken from the National Educational Longitudinal Study of 1988 , (NELS:88), utilizing structural equation modeling techniques. This study found support for the importance of educational engagement as a factor in understanding academic achievement. The Participation-Identification model was particularly well fitting when applied to the sample of high school completers, dropouts (both overall and White dropouts) and African-American students. This study also confirmed the contribution of school environmental factors (i.e., size, diversity of economic and ethnic status among students) and family resources (i.e., availability of learning resources in the home and parent educational level ) to students' educational engagement. Based on these findings, school social workers will need to be more attentive to utilizing macro-level interventions (i.e., community organization, interagency coordination) to achieve the organizational restructuring needed to address future challenges. The support found for the Participation-Identification model supports a shift in school social workers' attention from reactive attempts to improve the affective-interpersonal lives of students to proactive attention to their academic lives. The model concentrates school social work practices on the central mission of schools, which is educational engagement. School social workers guided by this model would be encouraged to seek changes in school policies and organization that would facilitate educational engagement.
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Wang, Yingqi. "Student Satisfaction Perceived Employability Skills, and Student Engagement: Structural Equation Modeling Analyses." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/99290.
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This study identified the relationships of student engagement with senior student
satisfaction and perceived employability skills from STEM fields in the U.S. A comparison of
the relationships of student engagement, student satisfaction, and perceived employability skills
was made across senior Asian international students and their American peers in STEM
programs. The National Study of Student Engagement (NSSE) data (2011) was used in this
study. Structural equation modeling analyses and invariance tests were employed to estimate
different models of student engagement, student satisfaction, and perceived employability skills
across different samples. The results found that both sense of support and relationships with
others of emotional engagement were found the most important constructs to predict college
student satisfaction and perceived employability skills. The cognitive engagement had a
significant positive effect on student perceived employability skills across all college students,
Asian international students, and American students in STEM education. Moreover, this study
identified the mediator role of student perceived employability skills on the relationship between
student engagement and student satisfaction for all three samples. Additionally, Asian
international students differed from American students regarding academic involvement,
participating in extracurricular activities, and sense of support in STEM education. Last but not
least, this study supported that the three-dimension student engagement model developed by
Fredricks et al. (2004) could apply to U.S. college students. Practical and theoretical implications
were discussed and limitations acknowledged.<br>Doctor of Philosophy<br>It is widely accepted that attracting STEM talents to the U.S. is a key element to maintain the United States' economic supremacy and competitive advantage in a global economy. Asian international students play a significant role to maintain a steady supply of STEM talent pipelines in the U.S. job market. The purpose of this study is to understand the relationships of student engagement with senior student satisfaction and perceived employability skills from STEM fields in the U.S. This study This study was also to identify the relationships of student engagement, student satisfaction, and perceived employability skills across senior Asian international students and their American peers in STEM programs. The results found that both sense of support and relationships with others of emotional engagement were the most important factors to predict college student satisfaction and perceived employability skills. Cognitive engagement had a significant positive influence on student perceived employability skills across all college students, Asian international students, and American students in STEM education. Moreover, this study identified the mediator role of student perceived employability skills on the relationship between student engagement and student satisfaction. Additionally, Asian international students differed from American students regarding academic involvement, participating in extracurricular activities, and sense of support in STEM education. Last but not least, this study supported that the three-dimension student engagement model could apply to U.S. college students. Practical and theoretical implications were discussed and limitations acknowledged.
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Liu, Bing. "Causal Gene Network Inference from Genetical Genomics Experiments via Structural Equation Modeling." Diss., Virginia Tech, 2006. http://hdl.handle.net/10919/29060.
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The goal of this research is to construct causal gene networks for genetical genomics experiments using expression Quantitative Trait Loci (eQTL) mapping and Structural Equation Modeling (SEM). Unlike Bayesian Networks, this approach is able to construct cyclic networks, while cyclic relationships are expected to be common in gene networks. Reconstruction of gene networks provides important knowledge about the molecular basis of complex human diseases and generally about living systems.
In genetical genomics, a segregating population is expression profiled and DNA marker genotyped. An Encompassing Directed Network (EDN) of causal regulatory relationships among genes can be constructed with eQTL mapping and selection of candidate causal regulators. Several eQTL mapping approaches and local structural models were evaluated in their ability to construct an EDN. The edges in an EDN correspond to either direct or indirect causal relationships, and the EDN is likely to contain cycles or feedback loops. We implemented SEM with genetics algorithms to produce sub-models of the EDN containing fewer edges and being well supported by the data. The EDN construction and sparsification methods were tested on a yeast genetical genomics data set, as well as the simulated data. For the simulated networks, the SEM approach has an average detection power of around ninety percent, and an average false discovery rate of around ten percent.<br>Ph. D.
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Nalin, Venkat Sameera. "Network Structural Equation Modeling of PV Minimodule Variants Under Indoor Accelerated Exposures." Case Western Reserve University School of Graduate Studies / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=case1619711989919366.
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VACCA, GIANMARCO. "Redundancy Analysis Models with Categorical Endogenous Variables: New Estimation Techniques Based on Vector GLM and Artificial Neural Networks." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2017. http://hdl.handle.net/10281/158304.
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I modelli ad equazioni strutturali con variabili latenti hanno subito un notevole sviluppo negli ultimi anni. Partendo dai pionieri delle due macro-definizioni di modelli con variabili latenti, Covariance Structure Analysis e Component Analysis, con LISREL e PLS-PM come le tecniche più importanti, diverse estensioni e miglioramenti sono stati proposti. Inoltre, per i modelli di analisi di ridondanza, che fanno parte della Component Analysis, ma hanno solo variabili endogene osservate, sono stati proposti nuovi metodi in letteratura per affrontare più di un gruppo di variabili osservate esogene, con equazioni lineari semplici ed un'ottimizzazione unificata del problema. La critica principale, che è stata affrontata di recente in nuovi filoni di letteratura riguardanti i modelli ad equazioni strutturali, è l'incapacità parziale di questi sistemi di equazioni di modellizzare indicatori categoriali. Sono stati proposti diversi metodi a tale scopo, in PLS-PM e LISREL rispettivamente, che sfruttano metodi di Optimal Scaling o l’algoritmo EM nel processo di ottimizzazione. Per l’analisi di ridondanza, con variabili endogene solo osservate, la possibilità di estendere le procedure di stima a variabili qualitative è notevolmente meno ostacolata da restrizioni del modello, ancor di più nel modello di analisi di ridondanza estesa, con più di un blocco di variabili esogene. Questo lavoro presenta una nuova stima di modelli di analisi di ridondanza estesa in presenza di variabili endogene binarie o categoriali, con due principali tecniche di stima: Iterated Reweighed Least Squares, e Gradient Descent con backpropagation tramite reti neurali. Per questi ultimi, recenti sviluppi nei modelli ad equazioni strutturali con reti neurali saranno esaminati, e la nuova tecnica sarà quindi introdotta.<br>Structural Equation Models with latent variables have considerably developed in recent years. Starting from the pioneers of the two most prominent ways of defining models with latent variables, namely Covariance Structure Analysis and Component Analysis, with LISREL and PLS-PM as the most famous techniques, several extensions and improvements have been put forward. Moreover, for Redundancy Analysis models, which are part of the Component Analysis framework, but have only observed endogenous variables, new methods have been proposed in literature to deal with more than one group of exogenous observed variables, with simple linear equations and a unified optimization problem. One main criticism, that has been dealt with recently in new strands of literature regarding Structural Equation Modeling, is the partial inability of these systems of linear equations to deal with categorical indicators. Several methods have been proposed, in PLS-PM and LISREL respectively, either related to Optimal Scaling, or adapting the EM algorithm to the particular case under examination. In the Redundancy Analysis framework, with only observed endogenous variables, the possibility of extending the estimation procedures to a qualitative setting is considerably less hampered by model restrictions, even more so in the Extended Redundancy Analysis model, with more than one block of exogenous variables. This work will hence present a new estimation of Extended Redundancy Analysis models in presence of binary or categorical endogenous variables, with two main estimation techniques: Iterated Reweighed Least Squares, and Gradient Descent with backpropagation in an Artificial Neural Network architecture. For the latter, recent developments in Structural Equation Models in the neural networks setting will be firstly examined, and the new technique will be subsequently introduced.
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McEnturff, Amber L. "Comparing Raw Score Difference, Multilevel Modeling, and Structural Equation Modeling Methods for Estimating Discrepancy in Dyads." Thesis, University of North Texas, 2020. https://digital.library.unt.edu/ark:/67531/metadc1703431/.
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The current study focused on dyadic discrepancy, the difference between two individuals. A Monte Carlo simulation was used to compare three dyadic discrepancy estimation methods across a variety of potential research conditions, including variations on intraclass correlation, cluster number, reliability, effect size, and effect size variance. The methods compared were: raw score difference (RSD); empirical Bayes estimate of slope in multilevel modeling (EBD); and structural equation modeling estimate (SEM). Accuracy and reliability of the discrepancy estimate and the accuracy of prediction when using the discrepancy to predict an outcome were examined. The results indicated that RSD and SEM, despite having poor reliability, performed better than EBD when predicting an outcome. The results of this research provide methodological guidance to researchers interested in dyadic discrepancies.
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George, Benjamin Thomas. "Extensions of the General Linear Model into Methods within Partial Least Squares Structural Equation Modeling." Thesis, University of North Texas, 2016. https://digital.library.unt.edu/ark:/67531/metadc862733/.
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The current generation of structural equation modeling (SEM) is loosely split in two divergent groups - covariance-based and variance-based structural equation modeling. The relative newness of variance-based SEM has limited the development of techniques that extend its applicability to non-metric data. This study focuses upon the extension of general linear model techniques within the variance-based platform of partial least squares structural equation modeling (PLS-SEM). This modeling procedure receives it name through the iterative PLS‑SEM algorithm's estimates of the coefficients for the partial ordinary least squares regression models in both the measurement model and the overall structural model. This research addresses the following research questions: (1) What are the appropriate measures for data segmentation within PLS‑SEM? (2) What are the appropriate steps for the analysis of rank-ordered path coefficients within PLS‑SEM? and (3) What is an appropriate model selection index for PLS‑SEM? The limited type of data to which PLS-SEM is applicable suggests an opportunity to extend the method for use with different data and as a result a broader number of applications. This study develops and tests several methodologies that are prevalent in the general linear model (GLM). The proposed data segmentation approaches posited and tested through post hoc analysis of structural model. Monte Carlo simulation allows demonstrating the improvement of the proposed model fit indices in comparison to the established indices found within the SEM literature. These posited PLS methods, that are logical transfers of GLM methods, are tested using examples. These tests enable demonstrating the methods and recommending reporting requirements.
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Woodruff, Elissa J. "Testing a Comprehensive Model of Muscle Dysmorphia Symptomatology in a Nonclinical Sample of Men." Thesis, University of North Texas, 2012. https://digital.library.unt.edu/ark:/67531/metadc149688/.
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As increasing emphases are placed on the importance of a muscular male physique in Westernized culture, more men are experiencing eating, exercise, and body image (EEBI) disturbances. Clinician-researchers have identified a syndrome, termed muscle dysmorphia (MD), in which individuals, usually men, are pathologically preoccupied with their perceived lack of muscularity. The current study tested a modified version of an extant theoretical model of MD symptomatology as well as an alternative model of MD symptomatology. Over 700 adult men completed a demographic questionnaire, a symptom inventory, a self-esteem questionnaire, a measure of perfectionism, a measure of the media’s influence on EEBI disturbances, and measures of body dissatisfaction and MD symptoms. Structural equation modeling (SEM) was used to examine the goodness of fit of the proposed models. Overall, the first model demonstrated poor fit with the data. Conversely, the alternative model fit the data adequately. The alternative model was cross validated with a second sample, and also fit this data adequately.
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Litson, Kaylee. "A Structural Equation Modeling Approach Combining Multitrait-Multimethod Designs with Moderated Mediation Analysis." DigitalCommons@USU, 2019. https://digitalcommons.usu.edu/etd/7541.
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Researchers who study clinical and developmental psychology are often interested in answering questions such as how interventions work, when treatment begins to improve health outcomes, or for whom treatment has the greatest impact. Answers to these and similar questions impact the general understanding of health and behavior, and can be imperative for effectively implementing intervention and prevention programs. To evaluate such complex relationships among variables, researchers have turned to moderated mediation analysis. Moderated mediation analysis is a statistical tool used to identify the conditional processes among observed or latent variables. However, in developmental and clinical psychology, variables are regularly measured using multiple sources or multiple methods. In fact, best practice recommendations in clinical psychology suggest measuring variables with multiple methods (Achenbach, 2006). The question arises how to use multimethod assessments in statistical analyses such as moderated mediation analysis. The objectives of the present study were to create a multimethod moderated mediation model, apply the model to an extant dataset of child developmental behaviors, and evaluate conditions under which the model performed well using a Monte Carlo simulation study. Results from the application showed that the indirect path from hyperactivity to academic impairment through oppositional defiant behavior was significant but not moderated by inattention. Results from the simulation study indicated that excluding true method effects from a moderated mediation model resulted in unacceptable parameter and standard error bias. These results point to the advantages of using the M4 model to evaluate moderated mediation in the presence of multimethod data.
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Rockwood, Nicholas John. "Estimating Multilevel Structural Equation Models with Random Slopes for Latent Covariates." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1554478681581538.
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Choo, Sangho. "Aggregate relationships between telecommunications and travel : structural equation modeling of time series data /." For electronic version search Digital dissertations database. Restricted to UC campuses. Access is free to UC campus dissertations, 2004. http://uclibs.org/PID/11984.
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Thesis (Ph.D. in Civil and Environmental Engineering)--University of California, Davis, 2004.<br>Cover title. Computer-produced typeface. Includes bibliographical references (p. 149-161). Also available via the World Wide Web. (Restricted to UC campuses)
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Peprah, Syvester. "On using AMOS, EQS, LISREL, Mx, RAMONA and SEPATH for structural equation modeling." Thesis, University of Port Elizabeth, 2000. http://hdl.handle.net/10948/279.
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Structural Equation Modeling is a common name for the statistical analysis of Structural Equation Models. Structural Equation Models are models that specify relationships between a set of variables and can be specified by means of path diagrams. A number of Structural Equation Modeling programs have been developed. These include, amongst others, AMOS, EQS, LISREL, Mx, RAMONA and SEPATH. A number of studies have been published on the use of some of the applications mentioned above. They include, amongst others, Brown (1986), Waller (1993) and Kano (1997). Structural Equation Models are increasingly being used in the social, economic and behavioral sciences. More and more people are therefore making use of one or more of the Structural Equation Modeling applications on the market. This study is performed with the aim of using each of the Structural Equation Modeling applications AMOS, EQS, LISREL, Mx, RAMONA and SEPATH for the first time and document the experience, joy and the difficulties encountered while using them. This treatise is different from the comparisons already published in that it is based on the use of AMOS, EQS, LISREL, Mx, RAMONA and SEPATH to fit a Structural Equation Model for peer influences on ambition, which is specified for data obtained by Duncan, Haller and Portes (1971), by myself as a first time user of each of the programs mentioned. The impressive features as well as the difficulties encountered are listed for each application. Recommendations for possible improvements to the various applications are also proposed. Finally, recommendations for future studies on the use of Structural Equation Modeling programs are made.
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Stripling, Gwendolyn D. "An Empirical Assessment of Energy Management Information System Success Using Structural Equation Modeling." NSUWorks, 2017. http://nsuworks.nova.edu/gscis_etd/1019.
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The Energy Industry utilizes Energy Management Information Systems (EMIS) smart meters to monitor utility consumers’ energy consumption, communicate energy consumption information to consumers, and to collect a plethora of energy consumption data about consumer usage. The EMIS energy consumption information is typically presented to utility consumers via a smart meter web portal. The hope is that EMIS web portal use will aid utility consumers in managing their energy consumption by helping them make effective decisions regarding their energy usage. However, little research exists that evaluates the effectiveness or success of an EMIS smart meter web portal from a utility consumer perspective. The research goal was to measure EMIS smart meter web portal success based on the DeLone and McLean Information Success Model. The objective of the study was to investigate the success constructs system quality, information quality, service quality, use, and user satisfaction, and determine their contribution to EMIS success, which was measured as net benefits. The research model used in this study employed Structural Equation Modeling (SEM) based on Partial Least Squares (PLS) to determine the validity and reliability of the measurement model and to evaluate the hypothetical relationships in the structural model. The significant validity and reliability measures obtained in this study indicate that the DeLone and McLean Information Success Model (2003) has the potential for use in future EMIS studies. The determinants responsible for explaining the variance in net benefits were EMIS use and user satisfaction. Based on the research findings, several implications and future research are stated and proposed.
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Jiang, Niantao Bollen Kenneth A. "Three tests of dimensionality in structural equation modeling a Monte Carlo simulation study /." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2006. http://dc.lib.unc.edu/u?/etd,476.
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Thesis (M.A.)--University of North Carolina at Chapel Hill, 2006.<br>Title from electronic title page (viewed Oct. 10, 2007). "... in partial fulfillment of the requirements for the degree of Master of Arts in the Department of Sociology." Discipline: Sociology; Department/School: Sociology.
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陳炳賢 and Ping-yin Jason Chan. "The role of avoidance in anxiety and depression: a structural equation modeling study." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B41547585.
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Oehlhof, Marissa Elena Wagner. "Self-Objectification among Overweight and Obese Women: An Application of Structural Equation Modeling." Bowling Green State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1320698865.
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Chan, Ping-yin Jason. "The role of avoidance in anxiety and depression a structural equation modeling study /." Click to view the E-thesis via HKUTO, 2008. http://sunzi.lib.hku.hk/hkuto/record/B41547585.
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Wang, Kairong. "Investigating the Domain of Geometric Inductive Reasoning Problems: A Structural Equation Modeling Analysis." Diss., CLICK HERE for online access, 2008. http://contentdm.lib.byu.edu/ETD/image/etd2385.pdf.
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Zhan, Huang-Ding, and 詹皇鼎. "Bayesian Structural Equation Modeling." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/09059007923002419208.
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碩士<br>銘傳大學<br>應用統計資訊學系碩士班<br>99<br>Many researchers from different fields are actively involved in the traditional Structural Equation Modeling (SEM) (classified as 1st generation, also called as the standard SEM), and tried to understand, learn and apply it. However, some scholars have already introduced the second generation of SEM (Lee, 2007). The standard SEM, in particular the LISREL model (Jöreskog and Sörbom, 1996), is composed of two components. The first component is a confirmatory factor analysis model (CFA) which consists of the latent variables to all their relating manifest variables and takes the measurement errors into account. This component can be regarded as a regression model which regresses the manifest variables with a small number of latent variables. The second component is a regression type structural equation which regresses the endogenous latent variables with the linear endogenous and exogenous latent variables.
In recent years, the growth of SEM has been very rapid. New models and statistical methods have been developed for better analyses of more complex data structures in practical research. Therefore, there is a need for the 2nd generation of SEM which involves a much wider class of SEM that include the standard SEM and their useful generations. The purpose of the study is to introduce the Bayesian SEM, and the research data is WHOQOL-BREF. After empirical testified, the analysis results from BSEM are really better than the traditional SEM, especially for factor loadings.
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Rademaker, Manuel Elias. "Composite-based Structural Equation Modeling." Doctoral thesis, 2020. https://doi.org/10.25972/OPUS-21593.
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Structural equation modeling (SEM) has been used and developed for decades across various domains and research fields such as, among others, psychology, sociology, and business research. Although no unique definition exists, SEM is best understood as the entirety of a set of related theories, mathematical models, methods, algorithms, and terminologies related to analyzing the relationships between theoretical entities -- so-called concepts --, their statistical representations -- referred to as constructs --, and observables -- usually called indicators, items or manifest variables. This thesis is concerned with aspects of a particular strain of research within SEM -- namely, composite-based SEM. Composite-based SEM is defined as SEM involving linear compounds, i.e., linear combinations of observables when estimating parameters of interest. The content of the thesis is based on a working paper (Chapter 2), a published refereed journal article (Chapter 3), a working paper that is, at the time of submission of this thesis, under review for publication (Chapter 4), and a steadily growing documentation that I am writing for the R package cSEM (Chapter 5). The cSEM package -- written by myself and my former colleague at the University of Wuerzburg, Florian Schuberth -- provides functions to estimate, analyze, assess, and test nonlinear, hierarchical and multigroup structural equation models using composite-based approaches and procedures. In Chapter 1, I briefly discuss some of the key SEM terminology. Chapter 2 is based on a working paper to be submitted to the Journal of Business Research titled “Assessing overall model fit of composite models in structural equation modeling”. The article is concerned with the topic of overall model fit assessment of the composite model. Three main contributions to the literature are made. First, we discuss the concept of model fit in SEM in general and composite-based SEM in particular. Second, we review common fit indices and explain if and how they can be applied to assess composite models. Third, we show that, if used for overall model fit assessment, the root mean square outer residual covariance (RMS_theta) is identical to another well-known index called the standardized root mean square residual (SRMR). Chapter 3 is based on a journal article published in Internet Research called “Measurement error correlation within blocks of indicators in consistent partial least squares: Issues and remedies”. The article enhances consistent partial least squares (PLSc) to yield consistent parameter estimates for population models whose indicator blocks contain a subset of correlated measurement errors. This is achieved by modifying the correction for attenuation as originally applied by PLSc to include a priori assumptions on the structure of the measurement error correlations within blocks of indicators. To assess the efficacy of the modification, a Monte Carlo simulation is conducted. The paper is joint work with Florian Schuberth and Theo Dijkstra. Chapter 4 is based on a journal article under review for publication in Industrial Management & Data Systems called “Estimating and testing second-order constructs using PLS-PM: the case of composites of composites”. The purpose of this article is threefold: (i) evaluate and compare common approaches to estimate models containing second-order constructs modeled as composites of composites, (ii) provide and statistically assess a two-step testing procedure to test the overall model fit of such models, and (iii) formulate recommendation for practitioners based on our findings. Moreover, a Monte Carlo simulation to compare the approaches in terms of Fisher consistency, estimated bias, and RMSE is conducted. The paper is joint work with Florian Schuberth and Jörg Henseler<br>Strukturgleichungsmodellierung (SEM) wird seit Jahrzehnten in verschiedenen Bereichen und Forschungsgebieten wie zum Beispiel der Psychologie, der Soziologie und den Wirtschaftswissenschaften verwendet und weiterentwickelt. SEM umfasst dabei die Gesamtheit einer Reihe verwandter Theorien, mathematischer Modelle, Methoden, Algorithmen und Terminologien im Zusammenhang mit der Analyse der Beziehungen zwischen theoretischen Entitäten - so genannten Konzepten -, ihrer statistischen Repräsentation - als Konstrukte bezeichnet - und Beobachtungsgrößen - üblicherweise Indikatoren, Items oder manifeste Variablen genannt. Diese Arbeit befasst sich mit Aspekten eines bestimmten Forschungszweigs innerhalb der SEM, den Komposit-basierten SEM Verfahren. Komposit-basiertes SEM ist ein Überbegriff für alle SEM Methoden, die Kompositen - d.h. gewichtete Linearkombinationen aus Beobachtungen - zur Schätzung unbekannter Größen verwenden. Der Inhalt der Arbeit basiert auf einem Arbeitspapier (Kapitel 2), einem veröffentlichten referierten Zeitschriftenartikel (Kapitel 3), einem weiteren Arbeitspapier (Kapitel 4) und einer stetig wachsenden Dokumentation, die ich für das R-Paket cSEM geschrieben habe, bzw. kontinuierlich weiterschreibe (Kapitel 5). Das Paket cSEM - geschrieben von mir und Florian Schuberth, meinem ehemaligen Kollegen an der Universität Würzburg - stellt Funktionen zur Verfügung, um lineare, nichtlineare, hierarchische und Multigruppen-Strukturgleichungsmodelle mit Hilfe von Komposit-basierten Ansätzen und Verfahren zu schätzen, zu analysieren, zu bewerten, zu testen und zu untersuchen. In Kapitel 1 gehe ich zunächst kurz auf einige der wichtigsten SEM Begriffe ein. Kapitel 2 basiert auf einem Arbeitspapier mit dem Titel „Assessing overall model fit of composite models in structural equation modeling“, das im Journal of Business Research eingereicht werden wird. Der Artikel befasst sich mit dem Thema der Bewertung der Gesamtgüte des Modells (eng. overall model fit) im Kontext des Komposit-Modells. Das Papier leistet drei zentrale Beiträge zur Literatur zu diesem Thema. Erstens wird das Konzept der Modellgüte in der SEM im Allgemeinen und der Komposit-basierten SEM im Besonderen eingehend erörtert. Zweitens wird auf gängige Fit-Indizes eingegangen und erläutert, ob und wie sie zur Beurteilung eines Komposit-Modells angewendet werden können. Drittens wird gezeigt, dass der root mean square outer residual covariance (RMS_theta) identisch mit einem anderen bekannten Index, dem standardized root mean square residual (SRMR) ist, falls der RMS_theta als Maß für die Modellanpassungsgüte verwendet werden soll. Kapitel 3 basiert auf einem in Internet Research veröffentlichten Zeitschriftenartikel mit dem Titel „Measurement error correlation within blocks of indicators in consistent partial least squares: Issues and remedies“. Der Artikel entwickelt das consistent partial least squares (PLSc) Verfahren weiter, um konsistente Parameterschätzungen für Populationsmodelle zu erhalten, deren Indikatorblöcke korrelierte Messfehler enthalten. Dies wird erreicht, indem die Korrektur für die Dämpfung (eng. attenuation), wie sie ursprünglich von PLSc angewandt wird, so modifiziert wird, dass sie a priori Annahmen über die Struktur der Messfehlerkorrelationen innerhalb der Indikatorblöcke enthält. Um die statistische Gültigkeit der Modifikation zu beurteilen, wird eine Monte Carlo Simulation durchgeführt. Das Papier wurde gemeinsam mit Florian Schuberth und Theo Dijkstra verfasst. Kapitel 4 basiert auf einem zur Veröffentlichung in Industrial Management & Data Systems anstehenden Zeitschriftenartikel mit dem Titel „Estimating and testing second order constructs using PLS-PM: the case of composites of composites“. Der Zweck dieses Artikels ist ein dreifacher: (i) Bewertung und Vergleich gängiger Ansätze zur Schätzung von Modellen, die Konstrukte zweiter Ordnung enthalten, die als Komposite von Kompositen modelliert wurden; (ii) ein zweistufiges Testverfahren vorzustellen und statistisch zu bewerten, um die allgemeine Modellanpassung solcher Modelle zu testen und (iii) auf der Grundlage unserer Ergebnisse Empfehlungen für Praktiker zu formulieren. Darüber hinaus wurde eine Monte Carlo Simulation durchgeführt, um die Ansätze in Bezug auf Fisher-Konsistenz, geschätzte Verzerrung und RMSE zu vergleichen. Das Papier wurde gemeinsam mit Florian Schuberth und Jörg Henseler verfasst. Kapitel 5 stellt das R-Paket cSEM vor. Zum Zeitpunkt der Einreichung dieser Dissertation zur Begutachtung ist cSEM im Comprehensive R Archive Network (CRAN) als Version 0.2.0 verfügbar
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Lim, Min. "Grobner Basis and Structural Equation Modeling." Thesis, 2010. http://hdl.handle.net/1807/26367.
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Structural equation models are systems of simultaneous linear equations that are generalizations of linear regression, and have many applications in the social, behavioural and biological sciences. A serious barrier to applications is that it is easy to specify models for which the parameter vector is not identifiable from the distribution of the observable data, and it is often difficult to tell whether a model is identified or not.
In this thesis, we study the most straightforward method to check for identification – solving a system of simultaneous equations. However, the calculations can easily get very complex. Grobner basis is introduced to simplify the process.
The main idea of checking identification is to solve a set of finitely many simultaneous
equations, called identifying equations, which can be transformed into polynomials. If a unique solution is found, the model is identified. Grobner basis reduces the polynomials into simpler forms making them easier to solve. Also, it allows us to investigate the model-induced constraints on the covariances, even when the model is not identified.
With the explicit solution to the identifying equations, including the constraints on the covariances, we can (1) locate points in the parameter space where the model is not identified, (2) find the maximum likelihood estimators, (3) study the effects of mis-specified models, (4) obtain a set of method of moments estimators, and (5) build customized parametric and distribution free tests, including inference for non-identified models.
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Mi, Xiaojuan. "Genetic applications using structural equation modeling." 2009. http://proquest.umi.com/pqdweb?did=1694433131&sid=3&Fmt=2&clientId=14215&RQT=309&VName=PQD.
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Thesis (Ph.D.)--University of Nebraska-Lincoln, 2009.<br>Title from title screen (site viewed June 26, 2009). PDF text: vii, 120 p. : ill. ; 855 Kb. UMI publication number: AAT 3350451. Includes bibliographical references. Also available in microfilm and microfiche formats.
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"Internet shopping: a structural equation modeling approach." 2001. http://library.cuhk.edu.hk/record=b5890711.
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So Sun-Yiu Sunny.<br>Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.<br>Includes bibliographical references (leaves 38-40).<br>Abstracts in English and Chinese.<br>ABSTRACT --- p.ii-iii<br>ACKNOLEDGEMENT --- p.iv<br>TABLE OF CONTENTS --- p.v<br>INTRODUCTION --- p.1-3<br>Internet in Hong Kong<br>LITERATURE REVIEW AND HYPOTHESES --- p.4-13<br>Theory of Reasoned Action (TRA)<br>Attitudes toward e-shopping<br>Perceived Social Norm<br>E-Shopping Experience<br>Social Economic Status (SES)<br>Internet Usage<br>Economic Motivation<br>Trust<br>Perceived Control<br>Channels matching<br>METHOD --- p.14-18<br>Procedure<br>Measures<br>RESULTS --- p.19-26<br>General Demographics<br>Technical Demographics<br>WWW and Internet Usage<br>Personal Information Disclosure<br>E-Shopping<br>Measurement Model<br>Structural Model<br>DISCUSSION --- p.27-37<br>Attitude and Social Norm<br>E-Shopping Experience<br>Channel Appropriateness<br>Intention for Future E-Shopping<br>Implications<br>Limitation and Future Research Direction<br>REFERENCE --- p.38-40<br>TABLE --- p.41-52<br>Table 1 to Table11<br>FIGURE --- p.53-59<br>Figure 1 to Figure5
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Lin, Tz-Jiun, and 林子鈞. "Apply Structural Equation Modeling and Fuzzy Theory." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/72605385682253868354.
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碩士<br>國立勤益科技大學<br>工業工程與管理系<br>100<br>With the development in economy and living quality, people expect houses to not only provide a living space, but also benefit their physical and mental health. In accordance, green houses have become more and more popular. This research thus aims to study the location selection for green houses. Through literature review, this research designs a needs analysis questionnaire based on the nine indicators and features of green houses. Then, descriptive analysis via SPSS 18.0 and model fitness analysis via SEM (AMOS 17.0) are implemented along with the Fuzzy theory to calculate the weight of each factor and to further examine the impact that each factor has on the location selection for green houses. According to the questionnaire analysis, this research discovers that people put a great emphasis on the closeness of green houses to parks or public green spaces, financial facilities, and schools. Also, among the nine indicators, people care more about natural ventilation, insulation against noises and natural lighting. These findings indicate that developers of green houses should pay more attention to those factors in order to build high quality green houses that meet people’s needs as well as achieve an optimal result that benefits the government, developers and consumers.
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Shields, Jennifer A. "Examining context effects using structural equation modeling /." 2003. http://wwwlib.umi.com/dissertations/fullcit/3083123.
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Schuberth, Florian. "Composite-based Methods in Structural Equation Modeling." Doctoral thesis, 2019. https://nbn-resolving.org/urn:nbn:de:bvb:20-opus-154653.
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This dissertation deals with composite-based methods for structural equation models with latent variables and their enhancement. It comprises five chapters. Besides a brief introduction in the first chapter, the remaining chapters consisting of four essays cover the results of my PhD studies.Two of the essays have already been published in an international journal. The first essay considers an alternative way of construct modeling in structural equation modeling.While in social and behavioral sciences theoretical constructs are typically modeled as common factors, in other sciences the common factor model is an inadequate way construct modeling due to its assumptions. This essay introduces the confirmatory composite analysis (CCA) analogous to confirmatory factor analysis (CFA). In contrast to CFA, CCA models theoretical constructs as composites instead of common factors. Besides the theoretical presentation of CCA and its assumptions, a Monte Carlo simulation is conducted which demonstrates that misspecifications of the composite model can be detected by the introduced test for overall model fit. The second essay rises the question of how parameter differences can be assessed in the framework of partial least squares path modeling. Since the standard errors of the estimated parameters have no analytical closed-form, the t- and F-test known from regression analysis cannot be directly used to test for parameter differences. However, bootstrapping provides a solution to this problem. It can be employed to construct confidence intervals for the estimated parameter differences, which can be used for making inferences about the parameter difference in the population. To guide practitioners, guidelines were developed and demonstrated by means of empirical examples. The third essay answers the question of how ordinal categorical indicators can be dealt with in partial least squares path modeling. A new consistent estimator is developed which combines the polychoric correlation and partial least squares path modeling to appropriately deal with the qualitative character of ordinal categorical indicators. The new estimator named ordinal consistent partial least squares combines consistent partial least squares with ordinal partial least squares. Besides its derivation, a Monte Carlo simulation is conducted which shows that the new estimator performs well in finite samples. Moreover, for illustration, an empirical example is estimated by ordinal consistent partial least squares. The last essay introduces a new consistent estimator for polynomial factor models. Similarly to consistent partial least squares, weights are determined to build stand-ins for the latent variables, however a non-iterative approach is used. A Monte Carlo simulation shows that the new estimator behaves well in finite samples<br>Die vorliegende Dissertation beschäftigt sich mit kompositenbasierten Schätzverfahren für Strukturgleichungsmodelle mit latenten Variablen sowie deren Weiterentwicklung und einhergehenden Problemen bei deren Verwendung in empirischen Studien. Die Arbeit umfasst insgesamt fünf Kapitel. Neben einer kurzen Einleitung im ersten Kapitel beinhalten die verbleibenden Kapitel Teile der Ergebnisse meiner Promotion, die in Form von vier, teilweise schon veröffentlichten Aufsätzen präsentiert werden. Der erste Aufsatz befasst sich mit einer alternativen Modellierungsweise der theoretischen Konstrukte in der Strukturgleichungsmodellierung. Während in den Sozial- und Verhaltenswissenschaften die theoretischen Konstrukte klassischerweise durch sogenannte common factors modelliert werden, stellt dies in manchen Situationen bzw. in anderen Wissenschaftsbereichen eine unplausible Annahme dar. In diesem Teil der Arbeit wird eine abgewandelte Form der konfirmatorischen Faktorenanalyse, die konfirmatorische Kompositenanalyse, vorgestellt, in welcher die theoretischen Konstrukte anstatt durch common factors mit Hilfe von Kompositen modelliert werden. Neben der Ausführung der theoretischen Grundlage wird durch eine Monte Carlo Simulation gezeigt, dass die konfirmatorische Kompositenanalyse geeignet ist, Fehlspezifikationen im zugrundeliegenden Kompositenmodell aufzudecken. In der zweiten Studie wird die Frage aufgeworfen, wie Parameterunterschiede im Rahmen der partial least squares Pfadmodellierung getestet werden können. Da die Standardfehler des Schätzers keine analytisch-geschlossene Form besitzen, kann der aus der Regressionsanalyse bekannte t- bzw. F-Test nicht direkt für die Beantwortung dieser Frage verwendet werden. Einen Ausweg bietet das Bootstrapping, durch welches Konfidenzintervalle um den geschätzten Parameterunterschied konstruiert werden können. Mit Hife dieser können statistische Aussagen über den Parameterunterschied in der Grundgesamtheit gemacht werden. Das vorgestellte Verfahren wird anhand eines empirischen Beispiels demonstriert. Der dritte Aufsatz dieser Arbeit geht der Frage nach, wie ordinale Indikatoren mit festen Kategorien in der partial least squares Pfadmodellierung berücksichtigt werden können. Es wird ein neues, konsistentes Schätzverfahren vorgestellt, das den qualitativen Charakter der ordinalen Variablen mittels der polychorischen Korrelation bei der Schätzung berücksichtigt. Der neue Schätzer trägt den Namen „ordinal consistent partial least squares“ und kombiniert die Verfahren consistent partial least squares und ordinal partial least squares. Neben der Darbietung des Schätzverfahrens wird mit Hilfe einer Monte Carlo Simulation gezeigt, dass das Verfahren ordinal consistent partial least squares geeignet ist, Modelle, die ordinale Indikatoren mit festen Kategorien enthalten, zu schätzen. Darüber hinaus wird ein empirisches Beispiel mit ordinal consistent partial least squares geschätzt. Das letzte Kapitel widmet sich der Schätzung nicht-linearer Strukturgleichungsmodelle mit latenten Variablen, wobei sich die Nichtlinearität auf die latenten Variablen und nicht auf deren Parameter bezieht. In diesem Kontext wird ein neues Schätzverfahren vorgestellt, welches ähnlich wie consistent partial least squares funktioniert und konsistente Parameterschätzungen für rekursive, nicht-lineare Gleichungssysteme liefert. Im Gegensatz zu consistent partial least squares benötigt der vorgestellte Momentenschätzer kein iteratives Verfahren, um die Gewichte für die Bildung der Kompositen zu bestimmen. Es wird mit Hilfe einer Monte Carlo Simulation gezeigt, dass der Schätzer geeignet ist, nicht-lineare Strukturgleichungsmodelle mit latenten Variablen zu schätzen
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"Comparing standardized indirect effects in structural equation modeling." 2007. http://library.cuhk.edu.hk/record=b5893372.
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Kwan, Lok Yin.<br>Thesis (M.Phil.)--Chinese University of Hong Kong, 2007.<br>Includes bibliographical references (leaves 80-83).<br>Abstracts in English and Chinese.<br>Chapter CHAPTER ONE: --- INTRODUCTION --- p.1<br>The basic mediation model --- p.1<br>General approaches in mediation analysis --- p.2<br>Resampling methods --- p.8<br>Comparing indirect effects --- p.9<br>A sequential model fitting method --- p.10<br>Current interest of study --- p.13<br>Chapter CHAPTER TWO: --- STANDARDIZATION OF PATH COEFFICIENTS --- p.15<br>Chapter CHAPTER THREE: --- COMPARING STANDARDIZED INDIRECT EFFECTS --- p.19<br>Chapter CHAPTER FOUR: --- REAL EXAMPLES --- p.28<br>Chapter CHAPTER FIVE: --- DISCUSSION --- p.55<br>Chapter CHAPTER SIX: --- CONCLUSION --- p.57<br>APPENDICES --- p.58<br>REFERENCES --- p.80
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Yang, Hsuan, and 楊玄. "Analyzing pilot fatigue using the structural equation modeling." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/82822855564901039789.
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碩士<br>國立臺灣海洋大學<br>航運管理學系<br>94<br>Flight fatigue is one of the key factors that affect flight safety. Cockpit crew of oceanic services with flight time of more than six hours experience sleep-loss and circadian rhythm disruption. Crew of short-haul services with flight time of less than two hours suffer from early departures, late finishes, and intensive takeoff and landing procedures that are workload demanding. Quantitative research is limited with respect to flight fatigue issues in Taiwan. The present research employed a structural equation modeling approach to conduct a path analysis and to identify the relationships among mental and physical fatigue, before and after flight duty.
The empirical study indicated that for oceanic crew mental fatigue (MF) before flight duty influenced MF after flight duty. MF after flight duty also influenced physical fatigue (PF) after flight duty. For regional operations (flight time between two and six hours), PF after flight duty is influenced by PF before flight duty and MF after duty is influenced by PF after duty. With respect to short-haul flights, MF after flight duty is influenced by MF before flight duty, PF after flight duty is influenced by both PF before flight duty and MF after flight duty.
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Chang, Chih-Jung, and 張志榮. "Gene Networks Reconstruction based on Structural Equation Modeling." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/21699798502766537048.
Full textAbstract:
碩士<br>臺灣大學<br>醫學工程學研究所<br>96<br>With the continual progress of human genome researches, more and more genes have been found to be closely related to human diseases. Accordingly, exploration of genetic functions has become one of major foci in biotechnology researches. It is well known that each gene does not work alone. Instead, it may involve enormous complicated interactions among genes in a biological process. Because of the complexity of physiological and biochemical processes in biology, the relations between the genes and most diseases are not clear currently. Therefore, the ultimate goal of gene networks reconstruction is to analyze the regulatory mechanisms among genes and understand how genes involve in biological processes.
Limited by the high cost of microarrays, most biological experiments can not offer a large number of observations for gene network reconstruction. To overcome this limitation, a new gene network model：linear dynamic factor model, which is based on structural equation modeling, is proposed in this study. Besides observed variables, linear dynamic factor model also incorporates hidden factors to depict regulations from proteins and other molecules that are not included in the gene networks but have influence on the gene networks. We simulated data from a 6-gene network with different observations to see the influence of the number of observations on the performance of the algorithm. We also applied the algorithm to microarray data to reconstruct the gene networks from focal adhesion pathway、SGS1 and its synthetic sick or lethal(SSL) partners and G2/M DNA damage checkpoint of Saccharomyces cerevisiae.
For the simulated data with 14 observations, the performance of the algorithm is well；for the simulated data with 52 observations, the performance of the algorithm is better than that of the simulated data with 14 observations. For the microarray data, the sensitivity or true positive rate can be in the neighborhood of 50%.
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YIN-NAN, CHEN, and 陳胤男. "Research of Applied Structural Equation Modeling in Corporate Branding." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/s9h654.
Full textAbstract:
碩士<br>南開科技大學<br>電子工程研究所<br>106<br>In recent years, with the food safety issues, product quality problems, product after-sales service, corporate integrity issues, corporate pollution problem are not for, resulting in many companies image in the minds of the masses, sense of responsibility and mission are discounted, people can not help but to corporate social responsibility perform left a big question mark? All these issues have shown that the current corporate social responsibility to fulfill the situation is not optimistic.
On corporate social responsibility of a lot of controversy and discussion undoubtedly brand assets is to establish and maintain worse, resulting in a lot of enterprises due to the social responsibility is not in place the brand assets plummeted, also be pulled into the vast number of consumer groups to the "black list". The development situation of the enterprises in our country, many enterprises for social responsibility to fulfill the lack of clear understanding and clarity of thought, enterprise more is the pursuit of immediate interests while ignoring the social responsibility, which brings the enterprise brand equity to sell at a discount greatly is currently, many enterprises in our country without Norine Ji. The reason is because of China's enterprises are generally lack of bear social responsibility determination and mechanism, the influence of corporate social responsibility on brand equity is the lack of comprehensive understanding and rational thinking.
The main research work and results of this study are summarized as follows:
First, social responsibility has significant impact on brand equity and dimensions. Some dimensions of social responsibility has a significant positive effect on brand equity, has significant effect on the perceived quality and brand association.
Second, the dimensions of social responsibility has a significant positive effect on brand equity and dimensions. Corporate environmental responsibility and brand assets and each dimension has a significant effect; corporate community responsibility the brand assets and brand association, perceived quality has significant influence; enterprises to fulfill their consumer responsibility on brand association, perception of quality has a significant impact.
Third, social responsibility to fulfill the process of enterprise brand equity, both the direct path and indirect path. The direct path performance for social responsibility directly affect brand equity, brand association and perceived quality; indirect path performance of social responsibility performance has a direct effect on the trust, and trust and dimensions of brand equity, brand association, perceived quality and brand loyalty honesty formed significant influence and indirect influence on brand equity through brand loyalty; in the different dimensions of corporate social responsibility on the brand assets and dimensions of the impact process and environmental responsibility brand loyalty through indirect effects of brand assets, in addition, to the brand assets have direct interaction. Only the community responsibility brand association has significant relationship. Consumer responsibility not only has a direct influence on brand association and perceived quality, but also has significant relationship on trust, and trust formation path significantly on brand equity and dimensions.
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"Implementing the analysis of two-level structural equation models in LISREL and Mx." 2006. http://library.cuhk.edu.hk/record=b5892795.
Full textAbstract:
Bai Yun.<br>Thesis (M.Phil.)--Chinese University of Hong Kong, 2006.<br>Includes bibliographical references (leaves 34-36).<br>Abstracts in English and Chinese.<br>Chapter 1 --- Introduction --- p.1<br>Chapter 2 --- The Analysis of a Two-Level SEM with Group Specific Variables in LISREL --- p.4<br>Chapter 2.1 --- The Model --- p.4<br>Chapter 2.2 --- An Augmented Model --- p.5<br>Chapter 2.3 --- Implementation in LISREL --- p.7<br>Chapter 2.4 --- Simulation --- p.9<br>Chapter 2.4.1 --- The Simulation Design --- p.9<br>Chapter 2.4.2 --- Methods of Evaluation --- p.10<br>Chapter 2.4.3 --- Simulation Results --- p.12<br>Chapter 2.5 --- A Comparison to Mplus --- p.14<br>Chapter 2.6 --- Empirical Demonstration: Multi-source Performance Appraisals --- p.14<br>Chapter 3 --- Implementing Two level SEM with Cross-level Covariance Structures in Mx --- p.16<br>Chapter 3.1 --- Two level Model Specifications with a Cross-level Covariance Structure --- p.17<br>Chapter 3.2 --- An Illustrative Example --- p.20<br>Chapter 3.3 --- Mx Simulation Design --- p.22<br>Chapter 3.4 --- Simulation Results --- p.23<br>Chapter 3.4.1 --- Accuracy of Parameter Estimates --- p.23<br>Chapter 3.4.2 --- Accuracy of Standard Error Estimates --- p.24<br>Chapter 3.4.3 --- Distribution of Goodness-of-fit Statistics --- p.24<br>Chapter 3.5 --- Enlarged Mx Model --- p.24<br>Chapter 3.5.1 --- Mx Model with Enlarged Xgi --- p.25<br>Chapter 3.5.2 --- Mx Model with Enlarged Ng --- p.26<br>Chapter 4 --- LISREL Sampling --- p.27<br>Chapter 4.1 --- LISREL Sampling Simulation Design --- p.27<br>Chapter 4.2 --- Simulation Results --- p.28<br>Chapter 4.2.1 --- Accuracy of Parameter Estimates --- p.29<br>Chapter 4.2.2 --- Accuracy of Standard Error Estimates --- p.30<br>Chapter 4.2.3 --- Distribution of Goodness-of-fit Statistics --- p.30<br>Chapter 5 --- Discussion --- p.31<br>Appendices --- p.37<br>Appendix 1 LISREL Sample Program --- p.37<br>Appendix 2 LISREL Syntax for an ALL-Y Model --- p.38<br>Appendix 3 LISREL Data Set Up --- p.39<br>Appendix 4 Mx Sample Program --- p.40<br>List of Figures<br>Chapter 1 --- The Augmented Two-level Model --- p.41<br>Chapter 2 --- Results of the Performance Appraisal Example --- p.42<br>Chapter 3 --- Two-level Model with a Cross-level Structure --- p.43<br>Chapter 4 --- QQ-plot for P1-P6 --- p.44<br>Chapter 5 --- QQ-plot for M1-M6 --- p.45<br>List of Tables<br>Chapter 1 --- Simulation Conditions Associated with Each Pattern --- p.46<br>Chapter 2 --- Simulation Results: Accuracy of Parameter Estimates --- p.47<br>Chapter 3 --- Simulation Results: Precision of Standard Error Estimates --- p.48<br>Chapter 4 --- Simulation Results: The Goodness-of-fit(GOF) Statistics --- p.49<br>Chapter 5 --- Analysis of the Performance Appraisal Example --- p.49<br>Chapter 6 --- Simulation Results: Mplus vs. LISREL-Parameter Estimates(l) --- p.50<br>Chapter 7 --- Simulation Results: Mplus vs. LISREL-Parameter Estimates(2) --- p.51<br>Chapter 8 --- Simulation Results: Mplus vs. LISREL-SE Estimates (Ratio) --- p.52<br>Chapter 9 --- Simulation Results: Mplus vs. LISREL-GOF Statistics --- p.53<br>Chapter 10 --- Mx Illustrative Example Results --- p.53<br>Chapter 11 --- Mx Simulation Patterns --- p.53<br>Chapter 12 --- Mx Simulation Results: Accuracy of Parameter Estimates --- p.54<br>Chapter 13 --- Mx Simulation Results: MARB for Parameter and S.E. Estimates --- p.54<br>Chapter 14 --- Mx Simulation Results: Goodness-of-fit Statistics --- p.55<br>Chapter 15 --- Mx Simulation Results for M5 --- p.55<br>Chapter 16 --- Mx Simulation Results for M5 and M6: Goodness-of-fit Statistics --- p.56<br>Chapter 17 --- Mx Simulation Results for M6 --- p.56<br>Chapter 18 --- LISREL Sampling: Simulation Patterns --- p.56<br>Chapter 19 --- LISREL Sampling: Simulation Results for LI to L3 --- p.57<br>Chapter 20 --- LISREL Sampling: Simulation Results for L4 to L6 --- p.58<br>Chapter 21 --- LISREL Sampling: MARB for Parameter and S.E. Estimates --- p.59<br>Chapter 22 --- LISREL Sampling: Goodness-of-fit Statistics --- p.59
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"Meta-analysis for structural equation modeling: a two-stage approach." 2002. http://library.cuhk.edu.hk/record=b6073457.
Full textAbstract:
Cheung Wai-leung.<br>"July 2002."<br>Thesis (Ph.D.)--Chinese University of Hong Kong, 2002.<br>Includes bibliographical references (p. 110-129).<br>Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.<br>Mode of access: World Wide Web.<br>Abstracts in English and Chinese.
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"Testing mediating effects with structural equation modeling: problems and solutions." 2004. http://library.cuhk.edu.hk/record=b5892188.
Full textAbstract:
Lau Suk Yin Rebecca.<br>Thesis (M.Phil.)--Chinese University of Hong Kong, 2004.<br>Includes bibliographical references (leaves 111-117).<br>Abstracts in English and Chinese.<br>ABSTRACT (ENGLISH) --- p.i<br>ABSTRACT (CHINESE) --- p.iii<br>ACKNOWLEDGEMENT --- p.iv<br>TABLE OF CONTENTS --- p.v<br>LIST OF TABLES --- p.viii<br>LIST OF FIGURES --- p.ix<br>Chapter CHAPTER I --- INTRODUCTION --- p.1<br>Chapter CHAPTER II --- LITERATURE REVIEW --- p.6<br>Chapter 2.1 --- Definition of Mediating Effects --- p.6<br>Chapter 2.2 --- Approaches to Mediational Analyses --- p.12<br>Chapter 2.2.1 --- Correlation Approach --- p.13<br>Chapter 2.2.2 --- Hierarchical Regression Approach --- p.17<br>Chapter 2.2.3 --- SEM Approach --- p.39<br>Chapter 2.3 --- Summary --- p.44<br>Chapter CHAPTER III --- A TEST FOR THE SIGNIFICANCE OF MEDIATING EFFECTS IN SEM --- p.47<br>Chapter 3.1 --- A Significance Test for the Mediating Effects with SEM --- p.48<br>Chapter 3.1.1 --- Model without Mediating Effects --- p.48<br>Chapter 3.1.2 --- Model with Full Mediation --- p.49<br>Chapter 3.1.3 --- Model with Partial Mediation --- p.49<br>Chapter 3.1.4 --- Model with Suppression --- p.50<br>Chapter 3.2 --- Procedure for Testing the Significance of Mediating Effects in SEM --- p.50<br>Chapter 3.3 --- Summary --- p.56<br>Chapter CHAPTER IV --- MODEL COMPARISON IN SEM --- p.59<br>Chapter 4.2 --- Testing the Significance of Mediating Effects with ΔFIs --- p.61<br>Chapter CHAPTER V --- METHODOLOGY OF SIMULATION --- p.65<br>Chapter 5.1 --- Resampling Space Generation --- p.65<br>Chapter 5.2 --- Sample Generation and Method of Analysis --- p.67<br>Chapter CHAPTER VI --- SIMULATION RESULTS AND DISCUSSION --- p.73<br>Chapter 6.1 --- Simulation Results --- p.73<br>Chapter 6.1.1 --- Variance Explained by Model Characteristics --- p.73<br>Chapter 6.1.1.1 --- Variance Explained Under the Condition of No Mediation --- p.80<br>Chapter 6.1.1.2 --- Variance Explained Under the Condition of Mediating Effects at 0.1 --- p.81<br>Chapter 6.1.1.2.1 --- Variance Explained by Factor Loadings --- p.81<br>Chapter 6.1.1.2.2 --- Variance Explained by Sample Size --- p.82<br>Chapter 6.1.1.2.3 --- Variance Explained by Number of Items --- p.83<br>Chapter 6.1.1.2.4 --- "Variance Explained by 2-Way Interactions of Factor Loadings, Sample Size and Number of Items" --- p.83<br>Chapter 6.1.2 --- Correlation between FIs and ΔFIs --- p.84<br>Chapter 6.2 --- Simulation Result Discussion --- p.88<br>Chapter CHAPTER VII --- NUMERICAL EXAMPLE --- p.91<br>Chapter 7.1 --- Testing Mediating Effects in a Model in Past Literature --- p.91<br>Chapter 7.2 --- Summary --- p.94<br>Chapter CHAPTER VIII --- DISCUSSION --- p.96<br>Chapter 8.1 --- Limitations and Directions for Future Research --- p.101<br>APPENDIX<br>Chapter APPENDIX I --- Syntax for Testing the Significance of Mediating Effects (Unconstrained Model)<br>Chapter APPENDIX II --- Syntax for Testing the Significance of Mediating Effects (Constrained Model)<br>Chapter APPENDIX III --- Syntax for Testing Full Mediation --- p.106<br>Chapter APPENDIX IV --- "Syntax for Testing Mediating Effects in Model by Foley, Kidder & Powell (2002) (DV: Intentions to Leave) (Unconstrained Model)" --- p.107<br>Chapter APPENDIX V --- "Syntax for Testing Mediating Effects in Model by Foley, Kidder & Powell (2002) (DV: Intentions to Leave) (Constrained Model)" --- p.108<br>Chapter APPENDIX VI --- "Syntax for Testing Mediating Effects in Model by Foley, Kidder & Powell (2002) (DV: Perceived Career Prospects) (Unconstrained Model)" --- p.109<br>Chapter APPENDIX VII --- "Syntax for Testing Mediating Effects in Model by Foley, Kidder & Powell (2002) (DV: Perceived Career Prospects) (Constrained Model)" --- p.110<br>REFERENCES --- p.111
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Haloho, Oktani, and 歐妲妮. "An Investigation for Indonesia's Maritime Satisfaction via Structural Equation Modeling." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/746a68.
Full textAbstract:
碩士<br>國立中央大學<br>數學系<br>105<br>The current status of Indonesia's maritime power is
unsatisfactory. It is desirable to find the reasons and make
improvements. The main purpose of this study is to construct a
theoretical model to describe the relationship between the
maritime power and satisfaction of Indonesia's maritime. Based
on our analysis, we propose a priority list for variables needed to
improve Indonesia's maritime.