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Hong, Seong Eun; Monroe, Scott; Falk, Carl F. – Journal of Educational Measurement, 2020
In educational and psychological measurement, a person-fit statistic (PFS) is designed to identify aberrant response patterns. For parametric PFSs, valid inference depends on several assumptions, one of which is that the item response theory (IRT) model is correctly specified. Previous studies have used empirical data sets to explore the effects…
Descriptors: Educational Testing, Psychological Testing, Goodness of Fit, Error of Measurement
Falk, Carl F.; Monroe, Scott – Educational and Psychological Measurement, 2018
Lagrange multiplier (LM) or score tests have seen renewed interest for the purpose of diagnosing misspecification in item response theory (IRT) models. LM tests can also be used to test whether parameters differ from a fixed value. We argue that the utility of LM tests depends on both the method used to compute the test and the degree of…
Descriptors: Item Response Theory, Matrices, Models, Statistical Analysis
Pham, Duy N.; Wells, Craig S.; Bauer, Malcolm I.; Wylie, E. Caroline; Monroe, Scott – Applied Measurement in Education, 2021
Assessments built on a theory of learning progressions are promising formative tools to support learning and teaching. The quality and usefulness of those assessments depend, in large part, on the validity of the theory-informed inferences about student learning made from the assessment results. In this study, we introduced an approach to address…
Descriptors: Formative Evaluation, Mathematics Instruction, Mathematics Achievement, Middle School Students
Monroe, Scott – Journal of Educational and Behavioral Statistics, 2019
In item response theory (IRT) modeling, the Fisher information matrix is used for numerous inferential procedures such as estimating parameter standard errors, constructing test statistics, and facilitating test scoring. In principal, these procedures may be carried out using either the expected information or the observed information. However, in…
Descriptors: Item Response Theory, Error of Measurement, Scoring, Inferences
Cai, Li; Monroe, Scott – Measurement: Interdisciplinary Research and Perspectives, 2013
In this commentary, the authors congratulate Professor Alberto Maydeu-Olivares on his article [EJ1023617: "Goodness-of-Fit Assessment of Item Response Theory Models, Measurement: Interdisciplinary Research and Perspectives," this issue] as it provides a much needed overview on the mathematical underpinnings of the theory behind the…
Descriptors: Goodness of Fit, Item Response Theory, Models, Statistical Analysis
Monroe, Scott; Cai, Li – Educational and Psychological Measurement, 2014
In Ramsay curve item response theory (RC-IRT) modeling, the shape of the latent trait distribution is estimated simultaneously with the item parameters. In its original implementation, RC-IRT is estimated via Bock and Aitkin's EM algorithm, which yields maximum marginal likelihood estimates. This method, however, does not produce the…
Descriptors: Item Response Theory, Models, Computation, Mathematics
Hansen, Mark; Cai, Li; Monroe, Scott; Li, Zhen – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2014
It is a well-known problem in testing the fit of models to multinomial data that the full underlying contingency table will inevitably be sparse for tests of reasonable length and for realistic sample sizes. Under such conditions, full-information test statistics such as Pearson's X[superscript 2] and the likelihood ratio statistic G[superscript…
Descriptors: Goodness of Fit, Item Response Theory, Classification, Maximum Likelihood Statistics
Hansen, Mark; Cai, Li; Monroe, Scott; Li, Zhen – Grantee Submission, 2016
Despite the growing popularity of diagnostic classification models (e.g., Rupp, Templin, & Henson, 2010) in educational and psychological measurement, methods for testing their absolute goodness-of-fit to real data remain relatively underdeveloped. For tests of reasonable length and for realistic sample size, full-information test statistics…
Descriptors: Goodness of Fit, Item Response Theory, Classification, Maximum Likelihood Statistics
Monroe, Scott; Cai, Li – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2013
In Ramsay curve item response theory (RC-IRT, Woods & Thissen, 2006) modeling, the shape of the latent trait distribution is estimated simultaneously with the item parameters. In its original implementation, RC-IRT is estimated via Bock and Aitkin's (1981) EM algorithm, which yields maximum marginal likelihood estimates. This method, however,…
Descriptors: Item Response Theory, Maximum Likelihood Statistics, Statistical Inference, Models
Cai, Li; Monroe, Scott – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2014
We propose a new limited-information goodness of fit test statistic C[subscript 2] for ordinal IRT models. The construction of the new statistic lies formally between the M[subscript 2] statistic of Maydeu-Olivares and Joe (2006), which utilizes first and second order marginal probabilities, and the M*[subscript 2] statistic of Cai and Hansen…
Descriptors: Item Response Theory, Models, Goodness of Fit, Probability

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