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The Impact of Measurement Noninvariance across Time and Group in Longitudinal Item Response Modeling
In-Hee Choi – Asia Pacific Education Review, 2024
Longitudinal item response data often exhibit two types of measurement noninvariance: the noninvariance of item parameters between subject groups and that of item parameters across multiple time points. This study proposes a comprehensive approach to the simultaneous modeling of both types of measurement noninvariance in terms of longitudinal item…
Descriptors: Longitudinal Studies, Item Response Theory, Growth Models, Error of Measurement
Xiaowen Liu – International Journal of Testing, 2024
Differential item functioning (DIF) often arises from multiple sources. Within the context of multidimensional item response theory, this study examined DIF items with varying secondary dimensions using the three DIF methods: SIBTEST, Mantel-Haenszel, and logistic regression. The effect of the number of secondary dimensions on DIF detection rates…
Descriptors: Item Analysis, Test Items, Item Response Theory, Correlation
Gorney, Kylie; Wollack, James A. – Journal of Educational Measurement, 2023
In order to detect a wide range of aberrant behaviors, it can be useful to incorporate information beyond the dichotomous item scores. In this paper, we extend the l[subscript z] and l*[subscript z] person-fit statistics so that unusual behavior in item scores and unusual behavior in item distractors can be used as indicators of aberrance. Through…
Descriptors: Test Items, Scores, Goodness of Fit, Statistics
Güler Yavuz Temel – Journal of Educational Measurement, 2024
The purpose of this study was to investigate multidimensional DIF with a simple and nonsimple structure in the context of multidimensional Graded Response Model (MGRM). This study examined and compared the performance of the IRT-LR and Wald test using MML-EM and MHRM estimation approaches with different test factors and test structures in…
Descriptors: Computation, Multidimensional Scaling, Item Response Theory, Models
Stephanie M. Bell; R. Philip Chalmers; David B. Flora – Educational and Psychological Measurement, 2024
Coefficient omega indices are model-based composite reliability estimates that have become increasingly popular. A coefficient omega index estimates how reliably an observed composite score measures a target construct as represented by a factor in a factor-analysis model; as such, the accuracy of omega estimates is likely to depend on correct…
Descriptors: Influences, Models, Measurement Techniques, Reliability
Abdolvahab Khademi; Craig S. Wells; Maria Elena Oliveri; Ester Villalonga-Olives – SAGE Open, 2023
The most common effect size when using a multiple-group confirmatory factor analysis approach to measurement invariance is [delta]CFI and [delta]TLI with a cutoff value of 0.01. However, this recommended cutoff value may not be ubiquitously appropriate and may be of limited application for some tests (e.g., measures using dichotomous items or…
Descriptors: Factor Analysis, Factor Structure, Error of Measurement, Test Items
Jackson, Kayla – ProQuest LLC, 2023
Prior research highlights the benefits of multimode surveys and best practices for item-by-item (IBI) and matrix-type survey items. Some researchers have explored whether mode differences for online and paper surveys persist for these survey item types. However, no studies discuss measurement invariance when both item types and online modes are…
Descriptors: Test Items, Surveys, Error of Measurement, Item Response Theory
Metsämuuronen, Jari – Practical Assessment, Research & Evaluation, 2022
The reliability of a test score is usually underestimated and the deflation may be profound, 0.40 - 0.60 units of reliability or 46 - 71%. Eight root sources of the deflation are discussed and quantified by a simulation with 1,440 real-world datasets: (1) errors in the measurement modelling, (2) inefficiency in the estimator of reliability within…
Descriptors: Test Reliability, Scores, Test Items, Correlation
Hyunjung Lee; Heining Cham – Educational and Psychological Measurement, 2024
Determining the number of factors in exploratory factor analysis (EFA) is crucial because it affects the rest of the analysis and the conclusions of the study. Researchers have developed various methods for deciding the number of factors to retain in EFA, but this remains one of the most difficult decisions in the EFA. The purpose of this study is…
Descriptors: Factor Structure, Factor Analysis, Monte Carlo Methods, Goodness of Fit
Chalmers, R. Philip; Zheng, Guoguo – Applied Measurement in Education, 2023
This article presents generalizations of SIBTEST and crossing-SIBTEST statistics for differential item functioning (DIF) investigations involving more than two groups. After reviewing the original two-group setup for these statistics, a set of multigroup generalizations that support contrast matrices for joint tests of DIF are presented. To…
Descriptors: Test Bias, Test Items, Item Response Theory, Error of Measurement
Weicong Lyu; Chun Wang; Gongjun Xu – Grantee Submission, 2024
Data harmonization is an emerging approach to strategically combining data from multiple independent studies, enabling addressing new research questions that are not answerable by a single contributing study. A fundamental psychometric challenge for data harmonization is to create commensurate measures for the constructs of interest across…
Descriptors: Data Analysis, Test Items, Psychometrics, Item Response Theory
Sample Size and Item Parameter Estimation Precision When Utilizing the Masters' Partial Credit Model
Custer, Michael; Kim, Jongpil – Online Submission, 2023
This study utilizes an analysis of diminishing returns to examine the relationship between sample size and item parameter estimation precision when utilizing the Masters' Partial Credit Model for polytomous items. Item data from the standardization of the Batelle Developmental Inventory, 3rd Edition were used. Each item was scored with a…
Descriptors: Sample Size, Item Response Theory, Test Items, Computation
Ayse Bilicioglu Gunes; Bayram Bicak – International Journal of Assessment Tools in Education, 2023
The main purpose of this study is to examine the Type I error and statistical power ratios of Differential Item Functioning (DIF) techniques based on different theories under different conditions. For this purpose, a simulation study was conducted by using Mantel-Haenszel (MH), Logistic Regression (LR), Lord's [chi-squared], and Raju's Areas…
Descriptors: Test Items, Item Response Theory, Error of Measurement, Test Bias
Montserrat Beatriz Valdivia Medinaceli – ProQuest LLC, 2023
My dissertation examines three current challenges of international large-scale assessments (ILSAs) associated with the transition from linear testing to an adaptive testing design. ILSAs are important for making comparisons among populations and informing countries about the quality of their educational systems. ILSA's results inform policymakers…
Descriptors: International Assessment, Achievement Tests, Adaptive Testing, Test Items
Shaojie Wang; Won-Chan Lee; Minqiang Zhang; Lixin Yuan – Applied Measurement in Education, 2024
To reduce the impact of parameter estimation errors on IRT linking results, recent work introduced two information-weighted characteristic curve methods for dichotomous items. These two methods showed outstanding performance in both simulation and pseudo-form pseudo-group analysis. The current study expands upon the concept of information…
Descriptors: Item Response Theory, Test Format, Test Length, Error of Measurement