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Xue Zhang; Chun Wang – Grantee Submission, 2021
Among current state-of-art estimation methods for multilevel IRT models, the two-stage divide-and-conquer strategy has practical advantages, such as clearer definition of factors, convenience for secondary data analysis, convenience for model calibration and fit evaluation, and avoidance of improper solutions. However, various studies have shown…
Descriptors: Error of Measurement, Error Correction, Item Response Theory, Comparative Analysis
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Pampaka, Maria; Hutcheson, Graeme; Williams, Julian – International Journal of Research & Method in Education, 2016
Missing data is endemic in much educational research. However, practices such as step-wise regression common in the educational research literature have been shown to be dangerous when significant data are missing, and multiple imputation (MI) is generally recommended by statisticians. In this paper, we provide a review of these advances and their…
Descriptors: Data Analysis, Statistical Inference, Error of Measurement, Computation
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Köhler, Carmen; Pohl, Steffi; Carstensen, Claus H. – Educational and Psychological Measurement, 2015
When competence tests are administered, subjects frequently omit items. These missing responses pose a threat to correctly estimating the proficiency level. Newer model-based approaches aim to take nonignorable missing data processes into account by incorporating a latent missing propensity into the measurement model. Two assumptions are typically…
Descriptors: Competence, Tests, Evaluation Methods, Adults
Lin, Johnny Cheng-Han – ProQuest LLC, 2013
Many methods exist for imputing missing data but fewer methods have been proposed to test the missing data mechanism. Little (1988) introduced a multivariate chi-square test for the missing completely at random data mechanism (MCAR) that compares observed means for each pattern with expectation-maximization (EM) estimated means. As an alternative,…
Descriptors: Data Analysis, Statistical Inference, Error of Measurement, Probability
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Luo, Wen; Kwok, Oi-man – Journal of Educational and Behavioral Statistics, 2012
In longitudinal multilevel studies, especially in educational settings, it is fairly common that participants change their group memberships over time (e.g., students switch to different schools). Participant's mobility changes the multilevel data structure from a purely hierarchical structure with repeated measures nested within individuals and…
Descriptors: Mobility, Statistical Analysis, Models, Longitudinal Studies
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Reichardt, Charles S. – Multivariate Behavioral Research, 2011
Maxwell, Cole, and Mitchell (2011) demonstrated that simple structural equation models, when used with cross-sectional data, generally produce biased estimates of meditated effects. I extend those results by showing how simple structural equation models can produce biased estimates of meditated effects when used even with longitudinal data. Even…
Descriptors: Structural Equation Models, Statistical Data, Longitudinal Studies, Error of Measurement
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Winneke, Gerhard; Walkowiak, Jens; Kramer, Ursula – Psychology in the Schools, 2004
This paper comments on a critical review of cohort studies on PCB-related neurodevelopmental deficit in young children by D.V. Cicchetti, A.S. Kaufman, and S.S. Sparrow (CKS). Major points of criticism of CKS, namely alleged violation of statistical principles, presumed lack of clinical significance of findings, and alleged insufficient control of…
Descriptors: Epidemiology, Criticism, Statistical Inference, Validity