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Direct linkYang, Ji Seung; Zheng, Xiaying – Journal of Educational and Behavioral Statistics, 2018
The purpose of this article is to introduce and review the capability and performance of the Stata item response theory (IRT) package that is available from Stata v.14, 2015. Using a simulated data set and a publicly available item response data set extracted from Programme of International Student Assessment, we review the IRT package from…
Descriptors: Item Response Theory, Item Analysis, Computer Software, Statistical Analysis
Download full textCasabianca, Jodi M.; Lewis, Charles – Journal of Educational and Behavioral Statistics, 2015
Loglinear smoothing (LLS) estimates the latent trait distribution while making fewer assumptions about its form and maintaining parsimony, thus leading to more precise item response theory (IRT) item parameter estimates than standard marginal maximum likelihood (MML). This article provides the expectation-maximization algorithm for MML estimation…
Descriptors: Item Response Theory, Maximum Likelihood Statistics, Computation, Comparative Analysis
Braun, Henry; von Davier, Matthias – Large-scale Assessments in Education, 2017
Background: Economists are making increasing use of measures of student achievement obtained through large-scale survey assessments such as NAEP, TIMSS, and PISA. The construction of these measures, employing plausible value (PV) methodology, is quite different from that of the more familiar test scores associated with assessments such as the SAT…
Descriptors: Scores, Test Use, Measurement, Psychometrics
Yang, Ji Seung; Cai, Li – Journal of Educational and Behavioral Statistics, 2014
The main purpose of this study is to improve estimation efficiency in obtaining maximum marginal likelihood estimates of contextual effects in the framework of nonlinear multilevel latent variable model by adopting the Metropolis-Hastings Robbins-Monro algorithm (MH-RM). Results indicate that the MH-RM algorithm can produce estimates and standard…
Descriptors: Computation, Hierarchical Linear Modeling, Mathematics, Context Effect
Yang, Ji Seung; Cai, Li – Grantee Submission, 2014
The main purpose of this study is to improve estimation efficiency in obtaining maximum marginal likelihood estimates of contextual effects in the framework of nonlinear multilevel latent variable model by adopting the Metropolis-Hastings Robbins-Monro algorithm (MH-RM; Cai, 2008, 2010a, 2010b). Results indicate that the MH-RM algorithm can…
Descriptors: Computation, Hierarchical Linear Modeling, Mathematics, Context Effect
Yang, Ji Seung; Cai, Li – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2013
The main purpose of this study is to improve estimation efficiency in obtaining full-information maximum likelihood (FIML) estimates of contextual effects in the framework of a nonlinear multilevel latent variable model by adopting the Metropolis-Hastings Robbins-Monro algorithm (MH-RM; Cai, 2008, 2010a, 2010b). Results indicate that the MH-RM…
Descriptors: Context Effect, Computation, Hierarchical Linear Modeling, Mathematics
Tan, Cheng Yong – Cambridge Journal of Education, 2018
The present study examined indirect effects of principal leadership on the mathematics achievement of 254,475 15-year-old students from 10,313 schools in 32 OECD economies. Results showed that the students could be divided into three categories ("Disadvantaged," "Average," and "Privileged") differing in levels of…
Descriptors: Mathematics Achievement, Disadvantaged, Advantaged, Socioeconomic Status
Samuel, Robin – Educational Research, 2014
Background: Young females have been found to out-perform males in terms of grades and university degrees in many studies. At the same time, young women seem to exhibit lower levels of well-being compared with men. Interestingly, little work has evaluated the interplay between educational success and well-being. However, antecedents and…
Descriptors: Gender Differences, Well Being, Academic Achievement, Correlation
