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Ferrando, Pere J. – Psicologica: International Journal of Methodology and Experimental Psychology, 2015
The standard two-wave multiple-indicator model (2WMIM) commonly used to analyze test-retest data provides information at both the group and item level. Furthermore, when applied to binary and graded item responses, it is related to well-known item response theory (IRT) models. In this article the IRT-2WMIM relations are used to obtain additional…
Descriptors: Item Response Theory, Structural Equation Models, Goodness of Fit, Statistical Analysis
Guyon, Hervé; Tensaout, Mouloud – Measurement: Interdisciplinary Research and Perspectives, 2016
In this article, the authors extend the results of Aguirre-Urreta, Rönkkö, and Marakas (2016) concerning the omission of a relevant causal indicator by testing the validity of the assumption that causal indicators are entirely superfluous to the measurement model and discuss the implications for measurement theory. Contrary to common wisdom…
Descriptors: Causal Models, Structural Equation Models, Formative Evaluation, Measurement
Engelhard, George, Jr.; Wang, Jue – Measurement: Interdisciplinary Research and Perspectives, 2014
The authors of the Focus article pose important questions regarding whether or not performance-based tasks related to executive functioning are best viewed as reflective or formative indicators. Miyake and Friedman (2012) define executive functioning (EF) as "a set of general-purpose control mechanisms, often linked to the prefrontal cortex…
Descriptors: Executive Function, Cognitive Measurement, Structural Equation Models, Item Response Theory
Thissen, David – Measurement: Interdisciplinary Research and Perspectives, 2013
In this commentary, David Thissen states that "Goodness-of-fit assessment for IRT models is maturing; it has come a long way from zero." Thissen then references prior works on "goodness of fit" in the index of Lord and Novick's (1968) classic text; Yen (1984); Drasgow, Levine, Tsien, Williams, and Mead (1995); Chen and…
Descriptors: Goodness of Fit, Item Response Theory, Models, Statistical Analysis
Coromina, Lluis – Social Indicators Research, 2013
A crucial issue in the European Union (EU) is which policies should be regulated by EU and which ones by national governments. Given this situation it is interesting to study the citizens' preference for the level of political decision making. The interest of the paper is mainly empirical, which consists in the creation of a measure for…
Descriptors: Foreign Countries, Decision Making, Nationalism, Politics
Battauz, Michela; Bellio, Ruggero – Psychometrika, 2011
This paper proposes a structural analysis for generalized linear models when some explanatory variables are measured with error and the measurement error variance is a function of the true variables. The focus is on latent variables investigated on the basis of questionnaires and estimated using item response theory models. Latent variable…
Descriptors: Error of Measurement, Structural Equation Models, Computation, Item Response Theory
He, Qingping; Hayes, Malcolm; Wiliam, Dylan – Research Papers in Education, 2013
The accuracy of the results of the national tests in English, mathematics and science taken by 11-year olds in England has been a matter of much debate since their introduction in 1994, with estimates of the proportion of students incorrectly classified varying from 10 to 30%. Using live data from the 2009 and 2010 administration of the national…
Descriptors: Foreign Countries, National Curriculum, Accuracy, Classification
Yang, Mingan; Dunson, David B. – Psychometrika, 2010
Structural equation models (SEMs) with latent variables are widely useful for sparse covariance structure modeling and for inferring relationships among latent variables. Bayesian SEMs are appealing in allowing for the incorporation of prior information and in providing exact posterior distributions of unknowns, including the latent variables. In…
Descriptors: Structural Equation Models, Markov Processes, Item Response Theory, Bayesian Statistics
Edwards, Michael C. – Psychometrika, 2010
Item factor analysis has a rich tradition in both the structural equation modeling and item response theory frameworks. The goal of this paper is to demonstrate a novel combination of various Markov chain Monte Carlo (MCMC) estimation routines to estimate parameters of a wide variety of confirmatory item factor analysis models. Further, I show…
Descriptors: Structural Equation Models, Markov Processes, Factor Analysis, Item Response Theory
Waters, Stacey; Cross, Donna – School Psychology Quarterly, 2010
Connectedness to school, teachers, and family are all significant protective factors in adolescents' lives, yet the measurement of each varies considerably. This article describes the measurement properties of three composite scales of adolescent connectedness, adapted from the Add Health study and the California Healthy Kids Survey. These…
Descriptors: Adolescents, Item Response Theory, Student School Relationship, Validity
Woods, Carol M. – Multivariate Behavioral Research, 2009
Differential item functioning (DIF) occurs when an item on a test or questionnaire has different measurement properties for 1 group of people versus another, irrespective of mean differences on the construct. This study focuses on the use of multiple-indicator multiple-cause (MIMIC) structural equation models for DIF testing, parameterized as item…
Descriptors: Test Bias, Structural Equation Models, Item Response Theory, Testing
Allua, Shane; Stapleton, Laura M.; Beretvas, S. Natasha – Educational and Psychological Measurement, 2008
When assessing latent mean differences, researchers frequently do not explore possible heterogeneity within their data sets. Sources of differences may be functions of a nested data structure or heterogeneity in the form of unobserved classes of observations defined by a difference in factor means. In this study, the use of multilevel structural…
Descriptors: Structural Equation Models, Item Response Theory, Social Sciences, Multivariate Analysis
Wirth, R. J.; Edwards, Michael C. – Psychological Methods, 2007
The rationale underlying factor analysis applies to continuous and categorical variables alike; however, the models and estimation methods for continuous (i.e., interval or ratio scale) data are not appropriate for item-level data that are categorical in nature. The authors provide a targeted review and synthesis of the item factor analysis (IFA)…
Descriptors: Structural Equation Models, Markov Processes, Item Response Theory, Factor Analysis
Saderholm, Jon; Ronau, Robert; Brown, E. Todd; Collins, Gary – School Science and Mathematics, 2010
The Diagnostic Teacher Assessment in Mathematics and Science (DTAMS) was developed to measure the content knowledge and pedagogical content knowledge of middle-school teachers. Its reliability and validity were initially established by reviewing national standards for content and use of expert question writing teams and reviewers. DTAMS was…
Descriptors: Structural Equation Models, Mathematics Achievement, Pedagogical Content Knowledge, Item Response Theory
Hoshino, Takahiro; Shigemasu, Kazuo – Applied Psychological Measurement, 2008
The authors propose a concise formula to evaluate the standard error of the estimated latent variable score when the true values of the structural parameters are not known and must be estimated. The formula can be applied to factor scores in factor analysis or ability parameters in item response theory, without bootstrap or Markov chain Monte…
Descriptors: Monte Carlo Methods, Markov Processes, Factor Analysis, Computation
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