Academic literature on the topic 'Measurement error model, Rasch model, Latent variable'
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Journal articles on the topic "Measurement error model, Rasch model, Latent variable"
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Maier, Kimberly S. "A Rasch Hierarchical Measurement Model." Journal of Educational and Behavioral Statistics 26, no. 3 (2001): 307–30. http://dx.doi.org/10.3102/10769986026003307.
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In this article, a hierarchical measurement model is developed that enables researchers to measure a latent trait variable and model the error variance corresponding to multiple levels. The Rasch hierarchical measurement model (HMM) results when a Rasch IRT model and a one-way ANOVA with random effects are combined ( Bryk & Raudenbush, 1992 ; Goldstein, 1987 ; Rasch, 1960 ). This model is appropriate for modeling dichotomous response strings nested within a contextual level. Examples of this type of structure include responses from students nested within schools and multiple response strings nested within people. Model parameter estimates of the Rasch HMM were obtained using the Bayesian data analysis methods of Gibbs sampling and the Metropolis-Hastings algorithm ( Gelfand, Hills, Racine-Poon, & Smith, 1990 ; Hastings, 1970 ; Metropolis, Rosenbluth, Rosenbluth, Teller, & Teller, 1953 ). The model is illustrated with two simulated data sets and data from the Sloan Study of Youth and Social Development. The results are discussed and parameter estimates for the simulated data sets are compared to parameter estimates obtained using a two-step estimation approach.
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Baghaei, Purya, and Mona Tabatabaee Yazdi. "The Logic of Latent Variable Analysis as Validity Evidence in Psychological Measurement." Open Psychology Journal 9, no. 1 (2016): 168–75. http://dx.doi.org/10.2174/1874350101609010168.
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Background:Validity is the most important characteristic of tests and social science researchers have a general consensus of opinion that the trustworthiness of any substantive research depends on the validity of the instruments employed to gather the data.Objective:It is a common practice among psychologists and educationalists to provide validity evidence for their instruments by fitting a latent trait model such as exploratory and confirmatory factor analysis or the Rasch model. However, there has been little discussion on the rationale behind model fitting and its use as validity evidence. The purpose of this paper is to answer the question: why the fit of data to a latent trait model counts as validity evidence for a test?Method:To answer this question latent trait theory and validity concept as delineated by Borsboom and his colleagues in a number of publications between 2003 to 2013 is reviewed.Results:Validating psychological tests employing latent trait models rests on the assumption of conditional independence. If this assumption holds it means that there is a ‘common cause’ underlying the co-variation among the test items, which hopefully is our intended construct.Conclusion:Providing validity evidence by fitting latent trait models is logistically easy and straightforward. However, it is of paramount importance that researchers appreciate what they do and imply about their measures when they demonstrate that their data fit a model. This helps them to avoid unforeseen pitfalls and draw logical conclusions.
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Grilli, Leonardo, and Roberta Varriale. "Specifying Measurement Error Correlations in Latent Growth Curve Models With Multiple Indicators." Methodology 10, no. 4 (2014): 117–25. http://dx.doi.org/10.1027/1614-2241/a000082.
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In this tutorial paper we focus on a multi-item Latent Growth Curve model for modeling change across time of a latent variable measured by multiple items at different occasions: in the structural part the latent variable grows according to a random slope linear model, whereas in the measurement part the latent variable is measured at each occasion by a conventional factor model with time-invariant loadings. The specification of a multi-item Latent Growth Curve model involves several interrelated choices: indeed, the features of the structural part, such as the functional form of the growth, are linked to the features of the measurement part, such as the correlation structure across time of measurement errors. In the paper, we give guidelines on the specification of the variance-covariance structure of measurement errors. In particular, we investigate the empirical implications of different specification strategies through an analysis of student ratings collected in four academic years about courses of the University of Florence. In the application we compare three correlation structures (independence, lag-1, and compound symmetry), illustrating the differences in terms of substantive assumptions, model fit, and interpretability of the results.
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Bourke, Mary, Linda Wallace, Marlene Greskamp, and Lucy Tormoehlen. "Improving Objective Measurement in Nursing Research: Rasch Model Analysis and Diagnostics of the Nursing Students' Clinical Stress Scale." Journal of Nursing Measurement 23, no. 1 (2015): 1E—15E. http://dx.doi.org/10.1891/1061-3749.23.1.1.
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Background and Purpose: The purpose of this study is to use Rasch model diagnostics and analysis to understand survey item (questions) functioning of the Nursing Students' Clinical Stress Scale, a rating scale instrument developed by Whang (2002). Methods: A rating scale instrument originally written in Korean was translated into English and administered to a convenience sample of all junior (46) and senior (64) students at a large Midwest university. Results and Conclusions: Rasch model analysis provided the empirical evidence to support that the survey items measured the latent variable, stress. Diagnostic results indicated the need for improved category labeling. Clinical Relevance: It is imperative that nursing educators evaluate and facilitate inter- and intraprofessional relationships between students and staff/faculty as well as understand the student experience.
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Huang, Xianzheng, and Joshua M. Tebbs. "On Latent-Variable Model Misspecification in Structural Measurement Error Models for Binary Response." Biometrics 65, no. 3 (2008): 710–18. http://dx.doi.org/10.1111/j.1541-0420.2008.01128.x.
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Leus, Olga, and Anatoly Maslak. "MEASUREMENT AND ANALYSIS OF TEACHERS’ PROFESSIONAL PERFORMANCE." SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference 2 (May 25, 2018): 308–19. http://dx.doi.org/10.17770/sie2018vol1.3097.
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The relevance of the measurement and analysis of teachers’ professional performance is based on the fact that teachers largely determine the quality of education at schools. The measurement of the latent variable "teacher’s professional performance" is done within the framework of the theory of latent variables based on the Rasch model. It was shown that the set of indicators has a high differentiating ability. The results of the measurement of this latent variable are used to compare the quality of professional activities of teachers of mathematics, history, Russian language, and literature as well as primary school teachers. No statistically significant differences were found between the professional performance of teachers of mathematics, history, and primary school teachers. The quality of professional activity of teachers of Russian language and literature is lower. The results of the measurement of teachers’ professional performance were used for comparison of schools. As one would expect, the highest quality of professional performance of teachers is in high schools and lowest in the primary schools; secondary schools occupy an intermediate position. Teachers’ professional performance is defined operationally, using a set of indicators. This set of indicators can be adjusted to clarify the content of the latent variable "teacher’s professional performance".
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Doyle, Patrick J., William D. Hula, Malcolm R. McNeil, Joseph M. Mikolic, and Christine Matthews. "An Application of Rasch Analysis to the Measurement of Communicative Functioning." Journal of Speech, Language, and Hearing Research 48, no. 6 (2005): 1412–28. http://dx.doi.org/10.1044/1092-4388(2005/098).
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Purpose:The purposes of this investigation were to examine the construct dimensionality and range of ability effectively measured by 28 assessment items obtained from 3 different patient-reported scales of communicative functioning, and to provide a demonstration of how the Rasch approach to measurement may contribute to the definition of latent constructs and the development of instruments to measure them.Method:Item responses obtained from 421 stroke survivors with and without communication disorders were examined using the Rasch partial credit model. The dimensionality of the item pool was evaluated by (a) examining correlations of Rasch person ability scores obtained separately from each of the 3 scales, (b) iteratively excluding items exceeding mean square model fit criteria, and (c) using principal-components analysis of Rasch model residuals. The range of ability effectively measured by the item pool was examined by comparing item difficulty and category threshold calibrations to the distribution of person ability scores and by plotting the modeled standard error of person ability estimates as a function of person ability level.Results:The results indicate that most assessment items fit a unidimensional measurement model, with the notable exception of items relating to the use of written communication. The results also suggest that the range of ability that could be reliably measured by the current item pool was restricted relative to the range of ability observed in the patient sample.Conclusions:It is concluded that (a) a mature understanding of communicative functioning as a measurement construct will require further research, (b) patients with stroke-related communication disorders will be better served by the development of instruments measuring a wider range of communicative functioning ability, and (c) the theoretical and methodological tools provided by the Rasch family of measurement models may be productively applied to these efforts.
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Bazan, Bartolo. "A Rasch-Validation Study of a Novel Speaking Span Task." Shiken 24.1 24, no. 1 (2020): 1–21. http://dx.doi.org/10.37546/jaltsig.teval24.1-1.
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Working Memory refers to the capacity to temporarily retain a limited amount of information that is available for manipulation by higher-order cognitive processes. Several assessment instruments, such as the speaking span task, have been associated with the measurement of working memory span. However, despite the widespread use of the speaking span task, no study, to the best of my knowledge, has attempted to validate it using Rasch Measurement Theory. Rasch analysis can potentially shed light on the dimensionality of a complex construct such as working memory as well as examine whether a collection of items is working together to construct a coherent and reliable measure of a targeted population. This pilot study reports a Rasch analysis of a novel speaking span task, which was administered individually to 31 Japanese junior high school students and scored using a newly developed scoring system. Two separate analyses were conducted on the task: an analysis of the individual items using the Rasch dichotomous model and an analysis of the super items (sets) using the partial credit model. The results indicate that the task measures a coherent unidimensional latent variable and is thus a useful tool for measuring the construct. Moreover, Rasch analysis was shown to be suitable method for evaluating working memory tests.
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Smith, Bradley C., та William Spaniel. "Introducingν-CLEAR: a latent variable approach to measuring nuclear proficiency". Conflict Management and Peace Science 37, № 2 (2018): 232–56. http://dx.doi.org/10.1177/0738894217741619.
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The causes and consequences of nuclear proficiency are central to important questions in international relations. At present, researchers tend to use observable characteristics as a proxy. However, aggregation is a problem: existing measures implicitly assume that each indicator is equally informative and that measurement error is not a concern. We overcome these issues by applying a statistical measurement model to directly estimate nuclear proficiency from observed indicators. The resulting estimates form a new dataset on nuclear proficiency which we call ν-CLEAR. We demonstrate that these estimates are consistent with known patterns of nuclear proficiency while also uncovering more nuance than existing measures. Additionally, we demonstrate how scholars can use these estimates to account for measurement error by revisiting existing results with our measure.
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Flaherty, Brian P., and Yusuke Shono. "Many Classes, Restricted Measurement (MACREM) Models for Improved Measurement of Activities of Daily Living." Journal of Survey Statistics and Methodology 9, no. 2 (2021): 231–56. http://dx.doi.org/10.1093/jssam/smaa047.
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Abstract Scientists use latent class (LC) models to identify subgroups in heterogeneous data. LC models reduce an item set to a latent variable and estimate measurement error. Researchers typically use unrestricted LC models, which have many measurement estimates, yet scientific interest primarily concerns the classes. We present highly restricted LC measurement models as an alternate method of operationalization. MACREM (Many Classes, Restricted Measurement) models have a larger number of LCs than a typical unrestricted model, but many fewer measurement estimates. Goals of this approach include producing more interpretable classes and better measurement error estimates. Parameter constraints accomplish this structuring. We present unrestricted and MACREM model results using data on activities of daily living (ADLs) from a national survey (N = 3,485). We compare a four-class unrestricted model with a fourteen-class MACREM model. The four-class unrestricted model approximates a dimension of functional limitation. The fourteen-class model includes unordered classes at lower levels of limitation, but ordered classes at higher levels of limitation. In contrast to the four-class model, all measurement error rates are reasonably small in the fourteen-class model. The four-class model fits the data better, but the fourteen-class model is more parsimonious (forty-three versus twenty-five parameters). Three covariates reveal specific associations with MACREM classes. In multinomial logistic regression models with a no limitation class as the reference class, past 12-month diabetes only distinguishes low limitation classes that include cutting one’s own toenails as a limitation. It does not distinguish low limitation classes characterized by other common limitations. Past 12-month asthma and current disability status perform similarly, but for heavy housework and walking limitation classes, respectively. These limitation-specific covariate associations are not apparent in the unrestricted model analyses. Identifying such connections could provide useful information to advance theory and intervention efforts.
Dissertations / Theses on the topic "Measurement error model, Rasch model, Latent variable"
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SIMONETTO, ANNA. "Estimation procedures for latent variable models with psychological traits." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2010. http://hdl.handle.net/10281/17370.
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The starting point for this thesis is a concrete problem: to measure, using
statistical models, aspects of subjective perceptions and assessments and to
understand their dependencies. The objective is to study the
statistical properties of some estimators of the parameters of regression models
with variables affected by measurement errors. These models are widely
used in surveys based on questionnaires developed to detect subjective assessments
and perceptions with Likert-type scales. It is a highly debated topic,
as many of the relevant aspects in this field are not directly observable and
therefore the variables used to estimate them are affected by measurement
errors. The models with measurement errors were very thorough in literature. In this work we will
developed two of the most used approaches that the authors have with this topic. Obviously, according to the approach chosen,
different models were proposed to estimate the relationships between
variables affected by measurement error. After exposing the main features
of these models, the thesis focuses on providing an original contribution to
comparative analysis of the two presented approaches.
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Gurkan, Gulsah. "From OLS to Multilevel Multidimensional Mixture IRT: A Model Refinement Approach to Investigating Patterns of Relationships in PISA 2012 Data." Thesis, Boston College, 2021. http://hdl.handle.net/2345/bc-ir:109191.
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Thesis advisor: Henry I. Braun<br>Secondary analyses of international large-scale assessments (ILSA) commonly characterize relationships between variables of interest using correlations. However, the accuracy of correlation estimates is impaired by artefacts such as measurement error and clustering. Despite advancements in methodology, conventional correlation estimates or statistical models not addressing this problem are still commonly used when analyzing ILSA data. This dissertation examines the impact of both the clustered nature of the data and heterogeneous measurement error on the correlations reported between background data and proficiency scales across countries participating in ILSA. In this regard, the operating characteristics of competing modeling techniques are explored by means of applications to data from PISA 2012. Specifically, the estimates of correlations between math self-efficacy and math achievement across countries are the principal focus of this study. Sequentially employing four different statistical techniques, a step-wise model refinement approach is used. After each step, the changes in the within-country correlation estimates are examined in relation to (i) the heterogeneity of distributions, (ii) the amount of measurement error, (iii) the degree of clustering, and (iv) country-level math performance. The results show that correlation estimates gathered from two-dimensional IRT models are more similar across countries in comparison to conventional and multilevel linear modeling estimates. The strength of the relationship between math proficiency and math self-efficacy is moderated by country mean math proficiency and this was found to be consistent across all four models even when measurement error and clustering were taken into account. Multilevel multidimensional mixture IRT modeling results support the hypothesis that low-performing groups within countries have a lower correlation between math self-efficacy and math proficiency. A weaker association between math self-efficacy and math proficiency in lower achieving groups is consistently seen across countries. A multilevel mixture IRT modeling approach sheds light on how this pattern emerges from greater randomness in the responses of lower performing groups. The findings from this study demonstrate that advanced modeling techniques not only are more appropriate given the characteristics of the data, but also provide greater insight about the patterns of relationships across countries<br>Thesis (PhD) — Boston College, 2021<br>Submitted to: Boston College. Lynch School of Education<br>Discipline: Educational Research, Measurement and Evaluation
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Sundström, David. "On specification and inference in the econometrics of public procurement." Doctoral thesis, Umeå universitet, Nationalekonomi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-121681.
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In Paper [I] we use data on Swedish public procurement auctions for internal regularcleaning service contracts to provide novel empirical evidence regarding green publicprocurement (GPP) and its effect on the potential suppliers’ decision to submit a bid andtheir probability of being qualified for supplier selection. We find only a weak effect onsupplier behavior which suggests that GPP does not live up to its political expectations.However, several environmental criteria appear to be associated with increased complexity,as indicated by the reduced probability of a bid being qualified in the postqualificationprocess. As such, GPP appears to have limited or no potential to function as an environmentalpolicy instrument. In Paper [II] the observation is made that empirical evaluations of the effect of policiestransmitted through public procurements on bid sizes are made using linear regressionsor by more involved non-linear structural models. The aspiration is typically to determinea marginal effect. Here, I compare marginal effects generated under both types ofspecifications. I study how a political initiative to make firms less environmentally damagingimplemented through public procurement influences Swedish firms’ behavior. Thecollected evidence brings about a statistically as well as economically significant effect onfirms’ bids and costs. Paper [III] embarks by noting that auction theory suggests that as the number of bidders(competition) increases, the sizes of the participants’ bids decrease. An issue in theempirical literature on auctions is which measurement(s) of competition to use. Utilizinga dataset on public procurements containing measurements on both the actual and potentialnumber of bidders I find that a workhorse model of public procurements is bestfitted to data using only actual bidders as measurement for competition. Acknowledgingthat all measurements of competition may be erroneous, I propose an instrumental variableestimator that (given my data) brings about a competition effect bounded by thosegenerated by specifications using the actual and potential number of bidders, respectively.Also, some asymptotic results are provided for non-linear least squares estimatorsobtained from a dependent variable transformation model. Paper [VI] introduces a novel method to measure bidders’ costs (valuations) in descending(ascending) auctions. Based on two bounded rationality constraints bidders’costs (valuations) are given an imperfect measurements interpretation robust to behavioraldeviations from traditional rationality assumptions. Theory provides no guidanceas to the shape of the cost (valuation) distributions while empirical evidence suggeststhem to be positively skew. Consequently, a flexible distribution is employed in an imperfectmeasurements framework. An illustration of the proposed method on Swedishpublic procurement data is provided along with a comparison to a traditional BayesianNash Equilibrium approach.
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Mohanlal, Pramod. "Structural equation modelling." Diss., 1997. http://hdl.handle.net/10500/17475.
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Over the past two decades there has been an upsurge in interest in structural equation
modelling (SEM). Applications abound in the social sciences and econometrics, but
the use of this multivariate technique is not so common in public health research.
This dissertation discusses the methodology, the criticisms and practical problems of
SEM. We examine actual applications of SEM in public health research.
Comparisons are made between multiple regression and SEM and between factor
analysis and SEM. A complex model investigating the utilization of antenatal care
services (ANC) by migrant women in Belgium is analysed using SEM. The
dissertation concludes with a discussion of the results found and on the use of SEM
in public health research. Structural equation modelling is recommended as a tool for
public health researchers with a warning against using the technique too casually.<br>Mathematical Sciences<br>M. Sc. (Statistics)
Books on the topic "Measurement error model, Rasch model, Latent variable"
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Jackman, Simon. Measurement. Edited by Janet M. Box-Steffensmeier, Henry E. Brady, and David Collier. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780199286546.003.0006.
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This article shows that the words ‘behavioural’ and ‘behaviour’ turn out to be better measures as judged by tests of criterion and convergent validity. It specifically discusses measurement problems. Further, it pertains to statistical models that link latent variables and their observed indicators as measurement models. The success of measurement — the quality of the inferences provided by a measurement model — is usually assessed with reference to two key concepts: validity and reliability. The distinct uses of measures of latent variables are reported. The article then deals with the costs of ignoring measurement error. Additionally, a quick introduction to factor analysis, item-response models, and a very general class of latent variable models are briefly given. Moreover, it describes the inference for discrete latent variables and the measurement in a dynamic setting.
Book chapters on the topic "Measurement error model, Rasch model, Latent variable"
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Leitgöb, Heinz, Daniel Seddig, Peter Schmidt, Edward Sosu, and Eldad Davidov. "Longitudinal Measurement (Non)Invariance in Latent Constructs." In Measurement Error in Longitudinal Data. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198859987.003.0010.
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The chapter discusses the basic principles and core problems of latent variable panel modelling, with a focus on the specification of error structures and (the evaluation of) longitudinal measurement invariance. We address alternative specifications of autocorrelative error structures, and demonstrate how to decompose the indicators’ residual variances into indicator-specific and random error components. Furthermore, besides describing the conventional global testing strategy for measurement (non)invariance, we contribute to the literature by integrating theoretical and analytical elements not yet extensively discussed outside the respective disciplines. We (i) introduce response shift theory as viable theoretical basis for the occurrence of noninvariance across time; (ii) provide a detailed description of model and scale identification strategies, accompanied by a critical reflection of their potential to adequately detect noninvariant parameters; and (iii) discuss the concepts of partial and approximate measurement invariance as well as the decomposition of response shifts and true change as different strategies of how to deal with measurement noninvariance.