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Yoo, Keunyoung. "Probabilistic SEM : an augmentation to classical Structural equation modelling." Diss., University of Pretoria, 2018. http://hdl.handle.net/2263/66521.
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Structural equation modelling (SEM) is carried out with the aim of testing hypotheses
on the model of the researcher in a quantitative way, using the sampled data. Although
SEM has developed in many aspects over the past few decades, there are still numerous
advances which can make SEM an even more powerful technique. We propose representing
the nal theoretical SEM by a Bayesian Network (BN), which we would like to call a
Probabilistic Structural Equation Model (PSEM). With the PSEM, we can take things
a step further and conduct inference by explicitly entering evidence into the network and
performing di erent types of inferences. Because the direction of the inference is not an
issue, various scenarios can be simulated using the BN. The augmentation of SEM with
BN provides signi cant contributions to the eld. Firstly, structural learning can mine
data for additional causal information which is not necessarily clear when hypothesising
causality from theory. Secondly, the inference ability of the BN provides not only insight
as mentioned before, but acts as an interactive tool as the `what-if' analysis is dynamic.Mini Dissertation (MCom)--University of Pretoria, 2018.
Statistics
MCom
Unrestricted
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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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Cerqueira, Pedro Henrique Ramos. "Structural equation models applied to quantitative genetics." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-05112015-145419/.
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Causal models have been used in different areas of knowledge in order to comprehend the causal associations between variables. Over the past decades, the amount of studies using these models have been growing a lot, especially those related to biological systems where studying and learning causal relationships among traits are essential for predicting the consequences of interventions in such system. Graph analysis (GA) and structural equation modeling (SEM) are tools used to explore such associations. While GA allows searching causal structures that express qualitatively how variables are causally connected, fitting SEM with a known causal structure allows to infer the magnitude of causal effects. Also SEM can be viewed as multiple regression models in which response variables can be explanatory variables for others. In quantitative genetics studies, SEM aimed to study the direct and indirect genetic effects associated to individuals through information related to them, beyond the observed characteristics, such as the kinship relations. In those studies typically the assumptions of linear relationships among traits are made. However, in some scenarios, nonlinear relationships can be observed, which make unsuitable the mentioned assumptions. To overcome this limitation, this paper proposes to use a mixed effects polynomial structural equation model, second or superior degree, to model those nonlinear relationships. Two studies were developed, a simulation and an application to real data. The first study involved simulation of 50 data sets, with a fully recursive causal structure involving three characteristics in which linear and nonlinear causal relations between them were allowed. The second study involved the analysis of traits related to dairy cows of the Holstein breed. Phenotypic relationships between traits were calving difficulty, gestation length and also the proportion of perionatal death. We compare the model of multiple traits and polynomials structural equations models, under different polynomials degrees in order to assess the benefits of the SEM polynomial of second or higher degree. For some situations the inappropriate assumption of linearity results in poor predictions of the direct, indirect and total of the genetic variances and covariance, either overestimating, underestimating, or even assign opposite signs to covariances. Therefore, we conclude that the inclusion of a polynomial degree increases the SEM expressive power.Modelos causais têm sido muitos utilizados em estudos em diferentes áreas de conhecimento, a fim de compreender as associações ou relações causais entre variáveis. Durante as últimas décadas, o uso desses modelos têm crescido muito, especialmente estudos relacionados à sistemas biológicos, uma vez que compreender as relações entre características são essenciais para prever quais são as consequências de intervenções em tais sistemas. Análise do grafo (AG) e os modelos de equações estruturais (MEE) são utilizados como ferramentas para explorar essas relações. Enquanto AG nos permite buscar por estruturas causais, que representam qualitativamente como as variáveis são causalmente conectadas, ajustando o MEE com uma estrutura causal conhecida nos permite inferir a magnitude dos efeitos causais. Os MEE também podem ser vistos como modelos de regressão múltipla em que uma variável resposta pode ser vista como explanatória para uma outra característica. Estudos utilizando MEE em genética quantitativa visam estudar os efeitos genéticos diretos e indiretos associados aos indivíduos por meio de informações realcionadas aos indivíduas, além das característcas observadas, como por exemplo o parentesco entre eles. Neste contexto, é tipicamente adotada a suposição que as características observadas são relacionadas linearmente. No entanto, para alguns cenários, relações não lineares são observadas, o que torna as suposições mencionadas inadequadas. Para superar essa limitação, este trabalho propõe o uso de modelos de equações estruturais de efeitos polinomiais mistos, de segundo grau ou seperior, para modelar relações não lineares. Neste trabalho foram desenvolvidos dois estudos, um de simulação e uma aplicação a dados reais. O primeiro estudo envolveu a simulação de 50 conjuntos de dados, com uma estrutura causal completamente recursiva, envolvendo 3 características, em que foram permitidas relações causais lineares e não lineares entre as mesmas. O segundo estudo envolveu a análise de características relacionadas ao gado leiteiro da raça Holandesa, foram utilizadas relações entre os seguintes fenótipos: dificuldade de parto, duração da gestação e a proporção de morte perionatal. Nós comparamos o modelo misto de múltiplas características com os modelos de equações estruturais polinomiais, com diferentes graus polinomiais, a fim de verificar os benefícios do MEE polinomial de segundo grau ou superior. Para algumas situações a suposição inapropriada de linearidade resulta em previsões pobres das variâncias e covariâncias genéticas diretas, indiretas e totais, seja por superestimar, subestimar, ou mesmo atribuir sinais opostos as covariâncias. Portanto, verificamos que a inclusão de um grau de polinômio aumenta o poder de expressão do MEE.
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HUANG, BIN. "STATISTICAL ASSESSMENT OF THE CONTRIBUTION OF A MEDIATOR TO AN EXPOSURE OUTCOME PROCESS." University of Cincinnati / OhioLINK, 2001. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1005678075.
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Aten, Jason Erik. "Causal not confounded gene networks inferring acyclic and non-acyclic gene bayesian networks in mRNA expression studies using recursive v-structures, genetic variation, and orthogonal causal anchor structural equation models /." Diss., Restricted to subscribing institutions, 2007. http://proquest.umi.com/pqdweb?did=1563274791&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.
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Fagua, José Camilo. "Geospatial Modeling of Land Cover Change in the Chocó-Darien Global Ecoregion of South America: Assessing Proximate Causes and Underlying Drivers of Deforestation and Reforestation." DigitalCommons@USU, 2018. https://digitalcommons.usu.edu/etd/7362.
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The Chocó-Darien Global Ecoregion (CGE) in South America is one of 25 global biodiversity hotspots prioritized for conservation. I performed the first land-use and land-cover (LULC) change analysis for the entire CGE in this dissertation. There were three main objectives: 1) Select the best available imagery to build annual land-use and land-cover maps from 2001 to 2015 across the CGE. 2) Model LULC across the CGE to assess forest change trends from 2002 to 2015 and identify the effect of proximate causes of deforestation and reforestation. 3) Estimate the effects of underlying drivers on deforestation and reforestation across the CGE between 2002 and 2015. I developed annual LULC maps across the CGE from 2002 to 2015 using MODIS (Moderate Resolution Imaging Spectro radiometer) vegetation index products and random forest classification. The LULC maps resulted in high accuracies (Kappa = 0.87; SD = 0.008). We detected a gradual replacement of forested areas with agriculture and secondary vegetation (agriculture reverting to early regeneration of natural vegetation) across the CGE. Forest loss was higher between 2010-2015 when compared to 2002-2010. LULC change trends, proximate causes, and reforestation transitions varied according to administrative authority (countries: PanamanianCGE, Colombian CGE, and Ecuadorian CGE). Population growth and road density were underlying drivers of deforestation. Armed conflicts, Gross Domestic Product, and average annual rain were proximate causes and underlying drivers related reforestation.
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Jahanshahi, Kaveh. "Quantification of the influences of built-form upon travel of employed adults : new models based on the UK National Travel Survey." Thesis, University of Cambridge, 2017. https://www.repository.cam.ac.uk/handle/1810/267841.
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After decades of research, a host of analytical difficulties is still hindering our understanding of the influences of the built form on travel. The main challenges are (a) assembling good quality data that reflects the majority of the known influences and that supports continuous monitoring, and (b) making sense methodologically of the many variables which strongly intercorrelate. This study uses the UK national travel survey (NTS) data that is among the most comprehensive of its form in the world. The fact that it has rarely been used so far for this purpose may be attributable to the methodological difficulties. This dissertation aims to develop a new analytical framework based on extended structural equation models (SEMs) in order to overcome some of the key methodological difficulties in quantifying the influences of the built form on travel, and in addition to provide a means to continuously monitor any changes in the effects over time. The analyses are focused on employed adults, because they are not only the biggest UK population segment with the highest per capita travel demand, but also the segment that are capable of adapting more rapidly to changing land use, built form and transport supply conditions. The research is pursued through three new models. Model 1 is a path diagram coupled with factor analyses, which estimates continuous, categorical and binary dependent variables. The model estimates the influences on travel distance, time and trip frequency by trip purpose while accounting for self-selection, spatial sorting, endogeneity of car ownership, and interactions among trip purposes. The results highlight stark differences among commuters, particularly the mobility disadvantages of women, part time and non-car owning workers even when they live in the most accessible urban areas. Model 2 incorporates latent categorisation analyses in order to identify a tangible typology of the built form and the associated variations in impacts on travel. Identifying NTS variables as descriptors for tangible built form categories provides an improved basis for investigating land use and transport planning interventions. The model reveals three distinct built form categories in the UK with striking variations in the patterns of influences. Model 3 further investigates the variations across the built form categories. The resulting random intercept SEM provides a more precise quantification of the influences of self-selection and spatial sorting across the built form categories for each socioeconomic group. Four research areas are highlighted for further studies: First, new preference, attitude and behavioural parameters may be introduced through incorporating non-NTS behavioural surveys; Second, the new SEMs provide a basis for incorporating choice modelling where the utility function is defined with direct, indirect and latent variables; Third, conceptual and methodological developments – such as non-parametric latent class analysis, allow expanding the current model to monitor changes in travel behaviour as and when new NTS or non NTS data become available. Fourth, the robustness of the inferences regarding causal or directional influences may require further quantification through designing new panel data sets, building on the findings above.
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Shami, Roland G. (Roland George) 1960. "Bayesian analysis of a structural model with regime switching." Monash University, Dept. of Econometrics and Business Statistics, 2001. http://arrow.monash.edu.au/hdl/1959.1/9277.
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Wegmann, Bertil. "Bayesian Inference in Structural Second-Price Auctions." Doctoral thesis, Stockholms universitet, Statistiska institutionen, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-57278.
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The aim of this thesis is to develop efficient and practically useful Bayesian methods for statistical inference in structural second-price auctions. The models are applied to a carefully collected coin auction dataset with bids and auction-specific characteristics from one thousand Internet auctions on eBay. Bidders are assumed to be risk-neutral and symmetric, and compete for a single object using the same game-theoretic strategy. A key contribution in the thesis is the derivation of very accurate approximations of the otherwise intractable equilibrium bid functions under different model assumptions. These easily computed and numerically stable approximations are shown to be crucial for statistical inference, where the inverse bid functions typically needs to be evaluated several million times. In the first paper, the approximate bid is a linear function of a bidder's signal and a Gaussian common value model is estimated. We find that the publicly available book value and the condition of the auctioned object are important determinants of bidders' valuations, while eBay's detailed seller information is essentially ignored by the bidders. In the second paper, the Gaussian model in the first paper is contrasted to a Gamma model that allows intrinsically non-negative common values. The Gaussian model performs slightly better than the Gamma model on the eBay data, which we attribute to an almost normal or at least symmetrical distribution of valuations. The third paper compares the model in the first paper to a directly comparable model for private values. We find many interesting empirical regularities between the models, but no strong and consistent evidence in favor of one model over the other. In the last paper, we consider auctions with both private-value and common-value bidders. The equilibrium bid function is given as the solution to an ordinary differential equation, from which we derive an approximate inverse bid as an explicit function of a given bid. The paper proposes an elaborate model where the probability of being a common value bidder is a function of covariates at the auction level. The model is estimated by a Metropolis-within-Gibbs algorithm and the results point strongly to an active influx of both private-value and common-value bidders.At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: Epub ahead of print. Paper 2: Manuscript. Paper 3: Manuscript. Paper 4: Manuscript.
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BRASIL, GUTEMBERG HESPANHA. "BAYESIAN DYNAMIC MODELLING THE CICLICAL COMPONENT IN STRUCTURAL MODEL FORMULATION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1989. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=8611@1.
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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOModelos estruturais para séries temporais vêm sendo bastante utilizados ultimamente e, adotam, basicamente, a mesma idéia da decomposição clássica de uma série temporal em seus componentes não-observáveis: tendência, sazonalidade, cíclica e irregular; para a componente cíclica, em particular, que é modelada por uma senóide a amortecida, existem apenas soluções no contexto da Estatística Clássica Harvey (1985). Neste trabalho discutimos extensivamente a solução Bayesiana para o modelo, tornando completamente estocástico a componente ciclo e obtendo um algoritmo para a estimação seqüencial dos parâmetros. A natureza não linear do problema é tratada pelos Modelos Dinâmicos Bayesianos; West e Harrison (1986).
The structural models for time series, so much in use today make use of the well know idea of decomposing a time series into its unobserved components of trend, seasonal, cycle and noise. The cyclical component in particular, which uses a damped sine wave to describe its moviment, has a clear solution available already in computer packages on the Classica framework of Harvey (1985). In this thesis we present a Bayesian solution to the cyclical component modelled by the same damped sine wave. The frequency and the damping factor, regarded as hyperparameters on the Classical solution are now incorporated to the system state vector and estimated by a sequential procedure. Finally, the non-linear nature of model is elegantly dealt with by the Bayesian Dynamic Models of West and Harrison (1986).
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Cunningham, Shaylyn, and University of Lethbridge Faculty of Education. "Anxiety, depression and hopelessness in adolescents : a structural equation model." Thesis, Lethbridge, Alta. : University of Lethbridge, Faculty of Education, 2005, 2006. http://hdl.handle.net/10133/344.
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This study tested a structural model, examining the relationship between a latent variable
termed demoralization and measured variables (anxiety, depression and hopelessness) in
a community sample of Canadian youth. The combined sample consisted of data
collected from four independent studies from 2001 to 2005. Nine hundred and seventy
one (n=971) participants in each of the previous four studies were high school students
(grades 10-12) from three geographic locations: Calgary, Saskatchewan and Lethbridge.
Participants completed a battery of self-report questionnaires including the Beck Anxiety
Inventory (BAI), Beck Depression Inventory-Revised (BDI-II), Beck Hopelessness Scale
(BHS), and demographic survey. Structural equation modeling was used for statistical
analysis. The analysis revealed that the final model, including depression, anxiety and
hopelessness and one latent variable demoralization, fit the data (chi-square value, X2 (2)
=7.24, p<. 001, goodness of fit indices (CFI=0.99, NFI=0.98) and standardized error
(0.05). Overall, the findings suggest that close relationships exist among depression,
anxiety, hopelessness and demoralization. In addition, the model was stable across
demographic variables: sex, grade, and location. Further, the model explains the
relationship between sub-clinical anxiety, depression and hopelessness. These findings
contribute to a theoretical framework, which has implications with educational and
clinical interventions. The present findings will help guide further preventative research
in examining demoralization as a precursor to sub-clinical anxiety and depression.xi, 127 leaves ; 29 cm.
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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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Moxley-Paquette, Elizabeth Ann. "Testing a Structural Equation Model of Language-based Cognitive Fitness." ScholarWorks, 2014. https://scholarworks.waldenu.edu/dissertations/1545.
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The normative development of language is often taken for granted, yet problems with language development can result in stress for the individual and family. A challenge with these language development problems lies within the contemporary education system, which assumes that children have appropriate skills when they begin school. The purpose of the study was to test a theoretical model of language readiness known as language-based cognitive fitness, which includes measures associated with structural concepts of language involving receptive language, expressive language, spontaneous narrative speech, and writing fluency. The sample included children from a private school who received an extensive battery of tests at admission and annually thereafter. Scores from a variety of cognitive measures were used in a structural equation modeling framework to test the model. Results demonstrated language-based cognitive fitness to be an interplay of verbal reasoning abilities, visual synthesis, and active analysis broadly representing receptive language, expressive language, spontaneous narrative expression, and writing fluency. Verbal reasoning, visual synthesis, and active analysis explained 91% of the variance in achievement. Implications for positive social change include an improved understanding for those who work with children's language development, specifically of the language structures responsible for language deficits and how these relate to overall cognitive fitness; interventions can be provided to help children more quickly make up language deficits.
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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(2) Procedural knowledge has a signitificant and positive direct effect on conditional knowledge
(3) Declarative knowledge has a positive indirect effect on conditional knowledge
(4) Knowledge of cognition significantly and positively influences procedural knowledge
(5) Regulation of cognition has a significant but negative direct effect on procedural knowledge
(6) Knowledge of cognition has positive indirect effects on conditional and procedural knowledge
(7) Regulation of cognition has negative indirect effects on conditional and procedural knowledge
(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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Busko, Deborah Ann. "Causes and consequences of perfectionism and procrastination, a structural equation model." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape15/PQDD_0004/MQ31814.pdf.
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Chandio, Fida Hussain. "Studying acceptance of online banking information system : a structural equation model." Thesis, Brunel University, 2011. http://bura.brunel.ac.uk/handle/2438/6153.
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Acceptance of information technology (IT) has remained a topic of interest for a last few decades. Several theories, specifically over the conceptualisation of the technology acceptance model (TAM) have emerged and they have been applied in different contexts to investigate new insights into the acceptance behaviour at individual and organisational levels. However, despite TAM’s maturity and validity in different contexts, very little published literature strives to extend its capability to predict individuals’ acceptance behaviour about an online banking information system (OBIS). A possible rational for this gap may be conceptualisation of the TAM under which individuals’ acceptance behaviour can only be predicted with two beliefs: perceived ease of use (PEOU) and perceived usefulness (PU). The evidence in literature shows that PU and PEOU beliefs are not sufficient; hence, they may not explain individuals’ acceptance behaviour in emerging contexts, such as online banking information systems, especially in developing economies such as Pakistan. There is therefore a need for inclusion of any additional factor that can enhance prediction of acceptance of online banking information system by potential users. Extending research on the TAM, this study developed and tested a model of OBIS acceptance. The proposed model integrated key constructs from the information systems acceptance research stream into the theoretical frame of the TAM and other theories from social psychology, such as the theory of reasoned action (TRA), theory of planned behaviour (TPB) and the TAM2. According to the proposed conceptual model, OBIS acceptance was determined by eight main factors, which included perceived usefulness, perceived ease of use, trust, technological self-efficacy, response time, output quality, accessibility, and terminology clarity. In this model, PU was hypothesised to be affected by PEOU, trust, technological self-efficacy (TSE), output quality (OQ) and response time (RT). In addition, PEOU was hypothesised to be determined by three external factors: TSE, accessibility and terminology clarity (TC). The model was tested on a sample of 353 Internet banking users in Pakistan. Using structural equation modelling with Analysis of Moment Structures (AMOS) software, data analysis showed considerable support for the extended hypothesised model. The result indicated that, in order of importance, PU, PEOU and trust explained 45.7 % of the variance in the acceptance behaviour. The trust and the TSE predicted 28.1 % of the variance in the PU. However, the hypothesised relationships between the PU and the PEOU, OQ and RT were found to be not significant. While in the PEOU, 21.8 % of the variance was predicted by the TSE, accessibility and TC. TSE was found to be a more influential determinant of the PEOU than the PU. The consideration of factors that have a significant influence on the acceptance of OBIS, as identified in this research, is important for the managers in the banking sector, especially in developing countries, in order to increase wider acceptance and use of these systems, which provide benefits to both the customers and the service providers.
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Dolan, Amanda Avery. "Synthesizing Undergraduate College Student Persistence: A Meta-analytic Structural Equation Model." Kent State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=kent1554756614807579.
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Craig, Stephen E. "A Structural Equation Model of Contributing Factors to Adolescent Social Interest." Thesis, University of North Texas, 1999. https://digital.library.unt.edu/ark:/67531/metadc2213/.
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The focus of the present study was to test through SEM the relationships between family influences (FI) and school influences (SI) on factors hypothesized to be associated with adolescent social interest: school belonging (SB), extracurricular participation (EP), and peer/romantic involvement (PRI). The final model consisted of FI and SI that contributed to the expression of adolescent social interest. FI included parental communication and parental caring. SI consisted of teacher fairness. SB consisted of a child's self-reported feelings of belonging at school, EP included self-reported involvement in sports or academic clubs, and PRI consisted of self-reported desire for romantic involvement or desire for participation with others. The proposed model suggested that FI contributed significantly to self-reported SB, EP, and PRI. Additionally, it was hypothesized that SI would contribute significantly to SB and EP, but not to PRI. The data used in the current study were part of an existing data set collected as part of the National Longitudinal Study on Adolescent Health. The total sample size for the present study was 2,561 male and female adolescents aged 12-19 years. The data consisted of adolescent and parent self-report information. Results suggested a significant relationship between FI and self-reported SB and PRI. As expected, a significant relationship existed between SI and SB. Also as expected, no significant relationship existed between SI and PRI. Neither the relationship between FI and EP nor SI and EP were significant. When analyzed separately, a significant relationship existed between SB and PRI; however, no significant relationship was found between SB and EP. Results also indicated several of the fit indices, including the average off-diagonal absolute standardized residual, the comparative fit index (CFI), and the Bentler-Bonett non-normed fit index (BBNFI), were a low to moderate fit. However, the final model was highly skewed and the model chi-square and chi-square were both exceptionally high, indicating the model appeared to moderately fit the data, but the need for further refinement is clear.
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Morris, Nathan J. "Multivariate and Structural Equation Models for Family Data." Case Western Reserve University School of Graduate Studies / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=case1247004562.
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Pyper, Jordan Daniel. "Estimation of the Effects of Parental Measures on Child Aggression Using Structural Equation Modeling." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3241.
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A child's parents are the primary source of knowledge and learned behaviors for developing children, and the benefits or repercussions of certain parental practices can be long lasting. Although parenting practices affect behavioral outcomes for children, families tend to be diverse in their circumstances and needs. Research attempting to ascertain cause and effect relationships between parental influences and child behavior can be difficult due to the complex nature of family dynamics and the intricacies of real life. Structural equation modeling (SEM) is an appropriate method for this research as it is able to account for the complicated nature of child-parent relationships. Both Frequentist and Bayesian methods are used to estimate the effect of latent parental behavior variables on child aggression and anxiety in order to allow for comparison and contrast between the two statistical paradigms in the context of structural equation modeling. Estimates produced from both methods prove to be comparable, but subtle differences do exist in those coefficients and in the conclusions to which a researcher would arrive. Although model estimates between the two paradigms generally agree, they diverge in the model selection process. The mother's behaviors are estimated to be the most influential on child aggression, while the influence of the father, socio-economic status, parental involvement, and the relationship quality of the couple also prove to be significant in predicting child aggression.
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Miller, Barbara Manning Boynton Lois A. "Issue advocacy to community stakeholders a structural equation model of potential outcomes /." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2006. http://dc.lib.unc.edu/u?/etd,134.
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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2006.Title from electronic title page (viewed Oct. 10, 2007). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the School of Journalism and Mass Communication." Discipline: Journalism and Mass Communication; Department/School: Journalism and Mass Communication, School of.
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Preacher, Kristopher J. "The Role of Model Complexity in the Evaluation of Structural Equation Models." The Ohio State University, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=osu1054130634.
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Reitzel-Jaffe, Deborah D. "Predicting relationship abuse, a structural equation model analysis of a social learning explanation." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/NQ28518.pdf.
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Zhang, Lei. "Social capital accumulation, business governance, and enterprise performance : a structural-equation-model approach /." View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?SOSC%202007%20ZHANG.
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Cao, Jing. "A structural equation model of customers' behavioural intentions in the Chinese restaurant sector." Thesis, University of Newcastle Upon Tyne, 2012. http://hdl.handle.net/10443/1504.
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The aim of this study is to develop a structural equation model (SEM) of customers’ behavioural intentions towards restaurant patronage in China. The study is set in the economic context of the Chinese open door policy of 1978 and the emergence of a service sector and middle class consumers with higher disposable incomes. The conceptual SEM is developed from the existing literature on customer loyalty, which includes constructs of perceived quality, sacrifice, perceived risk, perceived value, the Chinese cultural value of face, satisfaction, reputation, trust and behavioural intentions. A set of hypotheses concerning direct and indirect links between constructs is derived from the literature. The research methodology employs a self completion survey of customers of targeted restaurants that generated 489 valid responses. The questionnaire was designed with three thematic sections concerning restaurant visit behaviour, measures for each of the constructs, and respondents’ characteristics. Measurement scales for the constructs satisfied the minimum requirements of Cronbach’s alpha coefficient. The measurement models of the SEM constructs were evaluated using confirmatory factor analysis (CFA). They were accepted on the basis of measures of fit, the statistical significance and the signs of the coefficients. Preliminary analysis led to the modification of the conceptual SEM. The modified SEM was accepted on the basis of measures of fit, statistical significance and signs of coefficients, composite reliability, variance extracted and squared multiple correlation coefficients. Tests of hypotheses and tests for mediation provided for the analysis and decomposition of total effects on dependent constructs. The study establishes the relevance of traditional loyalty constructs, such as perceived quality, sacrifice, perceived risk, perceived value, satisfaction and reputation, and confirms the relevance of the Chinese cultural value of face. Total effect analysis reveals the importance of satisfaction, perceived value and perceived quality on customers’ behavioural intentions with associated benefits to commercial marketers in the hospitality sector.
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Scott, Colleen, Joel J. Hillhouse, and Rob Turrisi. "Student Column: Evaluating a Theoretical Model of Indoor Tanning Using Structural Equation Modeling." Digital Commons @ East Tennessee State University, 2014. https://dc.etsu.edu/etsu-works/55.
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Andrade, Joel T. "Psychosocial Precursors of Psychopathy in a Psychiatric Sample: A Structural Equation Model Analysis." Thesis, Boston College, 2009. http://hdl.handle.net/2345/1387.
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Thesis advisor: Thomas O'HarePsychopathy has received a marked increase in attention in the research literature over the past 2 decades since the validation and standardization of assessment tools designed to measure this construct, particularly the Psychopathy Checklist-measures (Hare, 1991/2003; Hart, Cox, & Hare, 1995; and Forth, Kosson, & Hare, 2003). Psychopathy has been identified as the best single predictor of violence among adult offenders (Hart, 1998). Such findings have led some to conclude that "psychopathy is the most important psychological construct for policy and practice in the criminal justice system" (Harris, Skilling, & Rice, 2001). Despite the overwhelming evidence of substantial societal and individual costs attributable to this disorder, little is known about psychosocial precursors of psychopathy. This study examines risk factors related to the development of psychopathy, as measured by the PCL:SV, in a sample of 446 psychiatric patients using structural equation modeling (SEM). The final SEM includes five predictor variables measuring early-life physical abuse, paternal antisocial behavior, and cognitive ability. Severe physical abuse (β = 0.17, p = .043), biological father's alcohol abuse history (β = .16, p =.004), biological father's arrest history (β = 0.13, p = .02), and the subject's cognitive ability (β = -0.18, p < .001) were found predictive of psychopathy in this sample. Post hoc analyses comparing male and female subjects, and black and white subjects, indicate different causal pathways in the development of psychopathy among these groups. Future research designed to assess these potentially different causal pathways are recommended. Implications to clinical theory, practice, and policy are also discussed
Thesis (PhD) — Boston College, 2009
Submitted to: Boston College. Graduate School of Social Work
Discipline: Social Work
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Galloway, David Bruce. "Prepotency of extrinsic and intrinsic factors on Job satisfaction: A structural equation model." CSUSB ScholarWorks, 2002. https://scholarworks.lib.csusb.edu/etd-project/2267.
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Prosser, Diane Johnson. "Cognitive complexity, problem solving skill, and career decision making : a structural equation model /." The Ohio State University, 1989. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487675687174987.
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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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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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Brandmaier, Andreas Markus [Verfasser], and Antonio [Akademischer Betreuer] Krüger. "Permutation distribution clustering and structural equation model trees / Andreas Markus Brandmaier. Betreuer: Antonio Krüger." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2012. http://d-nb.info/1051586631/34.
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Nusair, Khaldoon A. "A model of commitment in B-to-C travel context a structural equation modeling /." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1180541376.
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Monroe-Ossi, Heather M. "Complexities of Technology Integration in the Elementary Classroom Context: A Structural Equation Model Study." UNF Digital Commons, 2016. http://digitalcommons.unf.edu/etd/622.
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Effectively integrating technology into classroom instruction presents teachers with several dilemmas about their understanding of how students learn, their approach to designing learning activities, and their conceptualization of their role as teachers (Windschitl, 2002). Using the Technological Pedagogical Content Knowledge (TPACK) model (Koehler & Mishra, 2005, 2009; Mishra & Koehler, 2006) as the conceptual model undergirding the research, this study was designed to build evidence towards establishing the validity and reliability of a measurement instrument employed to assess the technological, pedagogical, and content knowledge teachers utilize, as well as gain an understanding of how this knowledge is affected by teacher beliefs about technology use in classroom practice. Three contextual factors were also investigated, namely leadership support for technology, teaching self-efficacy, and traditional beliefs about children. Structural equation modeling (SEM) was selected for analyzing data gathered in this research design. The relationships among four latent factors and three latent variables were examined using measurement models to determine a final structural model. Results (N = 75) suggest that the TPACK-deep scale has potential as a measure of teachers’ beliefs about their technological, pedagogical, and content knowledge. The findings yielded by the present exploratory study pertain to Design, Exertion, Ethics, and Proficiency—which are considered the four factors of the TPACK-deep scale (Kabakci-Yurdakul et al., 2012). Furthermore, this study’s findings indicate positive predictive relationships between leadership support for technology and teachers’ beliefs about using technology in their classrooms. While positive predictive relationships between teachers’ teaching self-efficacy and their beliefs about technology integration in classroom practice were found, no statistically significant association between teachers’ beliefs about using technology and their traditional beliefs about children could be established for three (Design, Exertion, Ethics) of the four TPACK-deep factors under investigation.
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Kavish, Daniel Ryan. "Interactionist Labeling: A Structural Equation Model of Formal Labeling, Juvenile Delinquency, and Adult Criminality." OpenSIUC, 2016. https://opensiuc.lib.siu.edu/dissertations/1311.
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This dissertation critically reviews prior labeling theory research concerning juvenile delinquency and adult criminality, and presents a structural equation model utilizing the National Longitudinal Study of Adolescent Health (Add Health). The labeling perspective is outlined as it was originally presented, and the theoretical elaborations that have taken place since are highlighted. Distinctions are made between formally applied criminal justice labels and the informal labels that are applied by significant others and parents. An interactionist labeling model that incorporates respondents’ levels of self-control is presented to explain formal labeling, levels of juvenile delinquency, and future criminality among a nationally representative sample of American adolescents: three waves of Add Health. The findings show that formal labeling was the strongest significant predictor of subsequent criminal involvement and that it mediated the effect of prior delinquency on subsequent criminal involvement.
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Brown, Chad M. "An Empirical Test of the Nontraditional Undergraduate Student Attrition Model Using Structural Equation Modeling." Ohio University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1176485072.
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Nusair, Khaldoon. "A model of commitment in B-to-C travel context: a structural equation modeling." The Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=osu1180541376.
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Brandmaier, Andreas Markus Verfasser], and Antonio [Akademischer Betreuer] [Krüger. "Permutation distribution clustering and structural equation model trees / Andreas Markus Brandmaier. Betreuer: Antonio Krüger." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:291-scidok-45459.
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Song, Yang. "A Livable City Study in China Using Structural Equation Models." Thesis, Uppsala universitet, Statistiska institutionen, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-154775.
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The concept of livable city was put forward naturally and began to gain more attention when people care more about human needs during the economic development. In this paper, we define a livable city as an urban area takes the residents' demand as first priority. It has a pleasant ecological environment, a mature community with rich public resources such as culture, transportation and medical system, and being economically well developed. Our study first reviews the theory development and literature on the subject. Then we set up a structural equation model (SEM) to verify the theory based on early works and find the dimensions that are important to the development of livable city. Using the data from China City Yearbook, 2007, a SEM analysis was performed. The result showed that a well developing economic system has positive influence on a city's livability.
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Kayan, Fadlelmula Fatma. "A Structural Model On 7th Grade Students." Phd thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613687/index.pdf.
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This study was conducted in an attempt to integrate a number of cognitive, motivational and behavioral factors in elementary mathematics education, and to develop a theoretical model that explains the direct and indirect relationships among these concepts and their underlying dimensions. In particular, it was intended to examine the interrelationships among students&rsquoachievement goal orientations, perception of classroom goal structure, self-efficacy, use of self-regulatory strategies, and academic achievement in mathematics. Participants were 1019 seventh grade students, enrolled in public elementary schools, located in four different urban and rural districts in Ankara. A self-report questionnaire and a mathematics achievement test were administered to the participants during their regular class periods. A pilot study was carried out with 250 seventh grade students, for conducting exploratory factor analysis. Structural equation modeling technique was used for data analysis. First, confirmatory factor analyses were conducted for each factor in the questionnaire. Then, a structural equation model was developed for the whole sample. Results revealed that students&rsquo
perceptions of classroom goal structure were directly linked to their adoption of achievement goal orientations. Among these goal orientations, only mastery goal orientation was associated with students&rsquo
use of learning strategies, which, in turn, related to their mathematics achievement. Among the learning strategies, only elaboration was significantly related to students&rsquo
mathematics achievement. Besides, self-efficacy was both directly and indirectly related to students&rsquo
adoption of achievement goals, use of learning strategies, and mathematics achievement.
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Smith, Kahsi Ann. "The development and testing of a social cognitive model of commitment : a structural equation analysis." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2009. http://wwwlib.umi.com/cr/syr/main.
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Osborne, Allan N. "Social conflict in construction-related inter-organizational collectives : a comparative analysis and structural equation model." Thesis, Northumbria University, 2005. http://nrl.northumbria.ac.uk/1875/.
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Irrespective of the groundswell of interest in construction industry conflict during the last two decades, there has been comparatively little research conducted that attempts to investigate the association between social conflict and ineffective construction industry inter-organizational relationships. This is despite the growing recognition that conditions conducive to effective social relationships between interdependent organizations contribute towards improved industrial productivity. This doctoral thesis contributes to the existing literature and empirical database on construction industry conflict by reporting the findings of a research project designed to explore the comparative organizational properties that encourage interdependence and the emergence of inter-organizational conflict during the construction process. The investigation builds upon and moderates an earlier comparative analysis of inter- organizational conflict by Molnar and Rogers (1979) in order to formulate a novel structural equation model. It includes as its database six case studies of medium- to large-scale new-build construction projects, selected from the north-eastern region of England, from which the networks of social relationships within the collectivities of construction-related organizations were examined from the perspective of the exogenous and endogenous comparative organizational properties. Primary data were collected during semi-structured interviews with twenty-three boundary role representatives of the twelve construction-related organizations responsible for the design and construction of the observed projects. The resultant structural equation model provides insight into the occurrence of inter-organizational conflict within the UK construction industry, in addition to explaining the key factors that influence the occurrence of ineffective construction industry inter-organizational relationships. In essence, this doctoral investigation has demonstrated the potential ability to predict the likelihood that social conflict will arise between interdependent construction- related organizations. Furthermore, it has paved the way for additional studies to be conducted to further understand the complex and intriguing aspects of construction industry inter-organizational relationships by presenting an accurately specified theoretical framework and an appropriately grounded methodological approach.
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Zulu, Sambo Lyson. "The impact of project management process quality on construction project performance : a structural equation model." Thesis, Heriot-Watt University, 2007. http://hdl.handle.net/10399/53.
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Sim, Yoon Young. "Motive-Goal Congruence, Imagination, and Well-Being: A Longitudinal Analysis with A Structural Equation Model." W&M ScholarWorks, 2018. https://scholarworks.wm.edu/etd/1530192821.
Full textAbstract:
The purpose of this study was to 1) examine individual differences in, and the 2) temporal precedence among, the motive-goal congruence, imagination, and well-being. I hypothesized that participants high in congruence will be high in spontaneous imagination and well-being assessments. For the temporal precedence, I proposed motive-goal congruence precedes spontaneous imagination and that spontaneous imagination precedes well-being. I employed the random intercepts cross-lagged panel model (RI-CLPM), the statistical model in which fully separate the within-person level from the between-person level. the current research partially supported the hypotheses with its detection of between-person level difference. Some possible reasons for the lack of support for the hypothesized lagged effects were discussed.
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"Bayesian criterion-based model selection in structural equation models." Thesis, 2010. http://library.cuhk.edu.hk/record=b6074920.
Full textAbstract:
Structural equation models (SEMs) are commonly used in behavioral, educational, medical, and social sciences. Lots of software, such as EQS, LISREL, MPlus, and WinBUGS, can be used for the analysis of SEMs. Also many methods have been developed to analyze SEMs. One popular method is the Bayesian approach. An important issue in the Bayesian analysis of SEMs is model selection. In the literature, Bayes factor and deviance information criterion (DIC) are commonly used statistics for Bayesian model selection. However, as commented in Chen et al. (2004), Bayes factor relies on posterior model probabilities, in which proper prior distributions are needed. And specifying prior distributions for all models under consideration is usually a challenging task, in particular when the model space is large. In addition, it is well known that Bayes factor and posterior model probability are generally sensitive to the choice of the prior distributions of the parameters. Furthermore the computational burden of Bayes factor is heavy. Alternatively, criterion-based methods are attractive in the sense that they do not require proper prior distributions in general, and the computation is quite simple. One of commonly used criterion-based methods is DIC, which however assumes the posterior mean to be a good estimator. For some models like the mixture SEMs, WinBUGS does not provide the DIC values. Moreover, if the difference in DIC values is small, only reporting the model with the smallest DIC value may be misleading. In this thesis, motivated by the above limitations of the Bayes factor and DIC, a Bayesian model selection criterion called the Lv measure is considered. It is a combination of the posterior predictive variance and bias, and can be viewed as a Bayesian goodness-of-fit statistic. The calibration distribution of the Lv measure, defined as the prior predictive distribution of the difference between the Lv measures of the candidate model and the criterion minimizing model, is discussed to help understanding the Lv measure in detail. The computation of the Lv measure is quite simple, and the performance is satisfactory. Thus, it is an attractive model selection statistic. In this thesis, the application of the Lv measure to various kinds of SEMs will be studied, and some illustrative examples will be conducted to evaluate the performance of the Lv measure for model selection of SEMs. To compare different model selection methods, Bayes factor and DIC will also be computed. Moreover, different prior inputs and sample sizes are considered to check the impact of the prior information and sample size on the performance of the Lv measure. In this thesis, when the performances of two models are similar, the simpler one is selected.Li, Yunxian.
Adviser: Song Xinyuan.
Source: Dissertation Abstracts International, Volume: 72-04, Section: B, page: .
Thesis (Ph.D.)--Chinese University of Hong Kong, 2010.
Includes bibliographical references (leaves 116-122).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Abstract also in Chinese.
46
"Bayesian diagnostics of structural equation models." 2013. http://library.cuhk.edu.hk/record=b5549717.
Full textAbstract:
行为学、社会学、心理学和医药学方面，结构方程模型(SEMs) 是研究有关潜在变量最常用的模型。这篇论文的目的是研究基本和高级结构方程模型的贝叶斯诊断，本文研究的结构方程模型包括非线性纺构方程模型、变换结构方程模型、二层结构方程模型和混合结构方程模型。基于对数贝叶斯因子的一阶与二阶局部影响测度是本文进行贝贝叶斯诊断的基础。局部影响测度的计算和模型参数估计是利用了蒙特卡洛(MCMC) 和扩展数据的方法。对比传统的基于极大似然的诊断，本文提出的贝叶斯诊断方法不仅能检测异常点或者影响点，而且可以诊断模型假设和先验设定的敏感性。 这些是通过对数据、模型假设和先验设定进行不同的扰动获得的 本文用大量的模拟实验来说明所提出的贝叶斯诊断方法的作用。 本文基于不同类型的结构方程模型，应用所提出的贝叶斯诊断方法于一些实际数据。In the behavioral, social, psychological, and medical sciences, the most widely used models in assessing latent variables are structural equation models (SEMs). This thesis aims to develop Bayesian diagnostic procedures for basic and advanced SEMs such as nonlinear SEMs, transformation SEMs, two-level SEMs, and mixture SEMs. The first- and second-order local inference measures with the objective functions defined based on the logarithm of Bayes factor are proposed to perform the Bayesian diagnostics. Markov chain Monte Carlo (MCMC) methods, along with data augmentation, are developed to compute the local influence measures and to estimate unknown model parameters. Compared with conventional maximum likelihood-based diagnostic procedures, the proposed Bayesian diagnostic approach can not only detect outliers or influential points in the observed data, but also conduct model comparison and sensitivity analysis by perturbing the data, sampling distributions, and the prior distributions of model parameters via a variety of perturbations. The empirical performances of the proposed Bayesian diagnostic procedures are revealed through extensive simulation studies. Several real-life data sets are used to illustrate the application of our proposed methodology in the context of different SEMs.
Detailed summary in vernacular field only.
Chen, Ji.
Thesis (Ph.D.)--Chinese University of Hong Kong, 2013.
Includes bibliographical references (leaves 130-135).
Abstract also in Chinese.
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- Structural equation models --- p.1
Chapter 1.2 --- Bayesian diagnostics --- p.3
Chapter 1.2.1 --- The first and second order local influence measures --- p.5
Chapter 1.2.2 --- A simple example --- p.9
Chapter 2 --- Bayesian diagnostics of nonlinear SEMs --- p.15
Chapter 2.1 --- Model description --- p.16
Chapter 2.2 --- Bayesian estimation and local inference of nonlinear SEMs --- p.17
Chapter 2.3 --- Simulation study --- p.24
Chapter 2.3.1 --- Simulation study 1 --- p.24
Chapter 2.3.2 --- Simulation study 2 --- p.25
Chapter 2.3.3 --- Simulation study 3 --- p.27
Chapter 2.4 --- Application: A study of kidney disease for type 2 diabetic patients --- p.29
Chapter 3 --- Bayesian diagnostics of transformation SEMs --- p.40
Chapter 3.1 --- Model description --- p.41
Chapter 3.2 --- Bayesian estimation and local inference of the transformation SEMs --- p.44
Chapter 3.3 --- Simulation study --- p.54
Chapter 3.3.1 --- Simulation study 1 --- p.54
Chapter 3.3.2 --- Simulation study 2 --- p.56
Chapter 3.4 --- Application: A study on the risk factors of osteoporotic fracture in older people --- p.58
Chapter 4 --- Bayesian diagnostics of two-level SEMs --- p.73
Chapter 4.1 --- Model description --- p.74
Chapter 4.2 --- Bayesian estimation and local inference of two-level SEMs --- p.75
Chapter 4.3 --- Simulation study --- p.88
Chapter 4.4 --- Application: A study of AIDS data --- p.91
Chapter 5 --- Bayesian diagnostics of mixture SEMs --- p.106
Chapter 5.1 --- Model description --- p.107
Chapter 5.2 --- Bayesian estimation and local inference ofmixture SEMs --- p.108
Chapter 5.3 --- Simulation study --- p.116
Chapter 5.3.1 --- Simulation study 1 --- p.116
Chapter 5.3.2 --- Simulation study 2 --- p.118
Chapter 6 --- Conclusion --- p.126
Bibliography --- p.130
Chapter A --- Proof of Theorem 1.1 and 1.2 --- p.136
Chapter B --- Full conditional distributions of the nonlinear SEM --- p.138
Chapter C --- Full conditional distributions of the transformation SEM --- p.141
Chapter D --- Full conditional distributions of the two-level SEM --- p.144
Chapter E --- AIDS preventative intervention data --- p.150
Chapter F --- Permutation sampler in the mixture SEM --- p.152
Chapter G --- Full conditional distributions of the mixture SEM --- p.153
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"Bayesian model selection for semiparametric structural equation models with modified group Lasso." 2014. http://repository.lib.cuhk.edu.hk/en/item/cuhk-1291541.
Full textAbstract:
Selecting an appropriate model is a crucial issue for applying structural equation models (SEMs) in real applications. Due to the model complexity, however, it is quite challenging to perform model selection on semiparametric SEMs with functional structural equations. In this thesis, we propose a modified Bayesian adaptive group Lasso procedure to perform model selection and estimation for semiparametric SEMs. By considering a novel formulation of basis expansions to approximate the unknown functions with certain penalties imposed, we are able to introduce a partial linear structure that combines the advantages of linear and nonparametric formulations for structural equations. The nonlinear, linear, or none structures in structural equations can be automatically detected with the proposed method. In addition, the group Lasso with adaptive penalties not only largely alleviates the model selection difficulties caused by the group effects and correlations introduced by basis expansions of latent variables, but also reduces the bias of traditional Lasso procedures. Simulation studies demonstrate that the proposed methodology performs satisfactorily. The proposed method is applied to analyze a real data set of diabetic kidney disease, which provides us some meaningful insights.在结构方程模型的实际应用中，选择一个合适的模型是一个核心问题。但是由于模型的复杂性，对于含有函数型结构的半参数结构方程模型进行模型选择十分困难。在本文中，我们提出了一种新的贝叶斯自适应群Lasso，并应用它来对半参数结构方程模型同时进行参数估计和模型选择。我们在非参数结构方程模型中引入了部分线性结构，并通过一种新的基底函数展开来近似结构方程里的未知函数。这种结构同时具备了线性模型和非参数模型的优势。本文的方法可以自动识别半参数结构方程模型里面的非线性和线性结构，并筛除不重要的变量。这种带有自适应惩罚的群Lasso不仅减小了传统Lasso方法在估计参数时产生的偏差，而且解决了由潜变量的基底表示导致的组效应和相关性引起的模型选择的困难。由模拟实验的结果可以看出本文提出的方法十分有效。我们还应用所提出的方法分析了一组关于糖尿病型肾病的数据，并得到了一些有意义的结果。
Feng, Xiangnan.
Thesis M.Phil. Chinese University of Hong Kong 2014.
Includes bibliographical references (leaves 51-56).
Abstracts also in Chinese.
Title from PDF title page (viewed on 18, October, 2016).
Detailed summary in vernacular field only.
48
"Bayesian analysis for complex structural equation models." 2000. http://library.cuhk.edu.hk/record=b6073291.
Full textAbstract:
Xin-Yuan Song."December 2000."
Thesis (Ph.D.)--Chinese University of Hong Kong, 2000.
Includes bibliographical references (p. 128-142).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Mode of access: World Wide Web.
Abstracts in English and Chinese.
49
"Bayesian approach for a multigroup structural equation model with fixed covariates." 2003. http://library.cuhk.edu.hk/record=b5891463.
Full textAbstract:
Oi-Ping Chiu.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.
Includes bibliographical references (leaves 45-46).
Abstracts in English and Chinese.
Chapter 1 --- Introduction --- p.1
Chapter 2 --- Model --- p.4
Chapter 2.1 --- General Model --- p.4
Chapter 2.2 --- Constraint --- p.5
Chapter 3 --- Bayesian Estimation via Gibbs Sampler --- p.7
Chapter 3.1 --- Conditional Distributions --- p.10
Chapter 3.2 --- Constraint --- p.15
Chapter 3.3 --- Bayesian Estimation --- p.16
Chapter 4 --- Model Comparison using the Bayes Factor --- p.18
Chapter 5 --- Simulation Study --- p.22
Chapter 6 --- Real Example --- p.27
Chapter 6.1 --- Model Selection --- p.29
Chapter 6.2 --- Bayesian Estimate --- p.30
Chapter 6.3 --- Sensitivity Analysis --- p.31
Chapter 7 --- Discussion --- p.32
Chapter A --- p.34
Bibliography --- p.45
50
"Bayesian statistical analysis for nonrecursive nonlinear structural equation models." Thesis, 2007. http://library.cuhk.edu.hk/record=b6074357.
Full textAbstract:
Keywords: Bayesian analysis, Finite mixture, Gibbs sampler, Langevin-Hasting sampler, MH sampler, Model comparison, Nonrecursive nonlinear structural equation model, Path sampling.Structural equation models (SEMs) have been applied extensively to management, marketing, behavioral, and social sciences, etc for studying relationships among manifest and latent variables. Motivated by more complex data structures appeared in various fields, more complicated models have been recently developed. For the developments of SEMs, there is a usual assumption about the regression coefficient of the underlying latent variables. On themselves, more specifically, it is generally assumed that the structural equation modeling is recursive. However, in practice, nonrecursive SEMs are not uncommon. Thus, this fundamental assumption is not always appropriate.
The main objective of this thesis is to relax this assumption by developing some efficient procedures for some complex nonrecursive nonlinear SEMs (NNSEMs). The work in the thesis is based on Bayesian statistical analysis for NNSEMs. The first chapter introduces some background knowledge about NNSEMs. In chapter 2, Bayesian estimates of NNSEMs are given, then some statistical analysis topics such as standard error, model comparison, etc are discussed. In chapter 3, we develop an efficient hybrid MCMC algorithm to obtain Bayesian estimates for NNSEMs with mixed continuous and ordered categorical data. Also, some statistical analysis topics are discussed. In chapter 4, finite mixture NNSEMs are analyzed with the Bayesian approach. The newly developed methodologies are all illustrated with simulation studies and real examples. At last, some conclusion and discussions are included in Chapter 5.
Li, Yong.
"July 2007."
Adviser: Sik-yum Lee.
Source: Dissertation Abstracts International, Volume: 69-01, Section: B, page: 0398.
Thesis (Ph.D.)--Chinese University of Hong Kong, 2007.
Includes bibliographical references (p. 99-111).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Abstracts in English and Chinese.
School code: 1307.