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Maria Bolsinova; Jesper Tijmstra; Leslie Rutkowski; David Rutkowski – Journal of Educational and Behavioral Statistics, 2024
Profile analysis is one of the main tools for studying whether differential item functioning can be related to specific features of test items. While relevant, profile analysis in its current form has two restrictions that limit its usefulness in practice: It assumes that all test items have equal discrimination parameters, and it does not test…
Descriptors: Test Items, Item Analysis, Generalizability Theory, Achievement Tests
Miguel A. García-Pérez – Educational and Psychological Measurement, 2024
A recurring question regarding Likert items is whether the discrete steps that this response format allows represent constant increments along the underlying continuum. This question appears unsolvable because Likert responses carry no direct information to this effect. Yet, any item administered in Likert format can identically be administered…
Descriptors: Likert Scales, Test Construction, Test Items, Item Analysis
DeCarlo, Lawrence T. – Journal of Educational Measurement, 2023
A conceptualization of multiple-choice exams in terms of signal detection theory (SDT) leads to simple measures of item difficulty and item discrimination that are closely related to, but also distinct from, those used in classical item analysis (CIA). The theory defines a "true split," depending on whether or not examinees know an item,…
Descriptors: Multiple Choice Tests, Test Items, Item Analysis, Test Wiseness
Tyrone B. Pretorius; P. Paul Heppner; Anita Padmanabhanunni; Serena Ann Isaacs – SAGE Open, 2023
In previous studies, problem solving appraisal has been identified as playing a key role in promoting positive psychological well-being. The Problem Solving Inventory is the most widely used measure of problem solving appraisal and consists of 32 items. The length of the instrument, however, may limit its applicability to large-scale surveys…
Descriptors: Problem Solving, Measures (Individuals), Test Construction, Item Response Theory
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
Jiaying Xiao; Chun Wang; Gongjun Xu – Grantee Submission, 2024
Accurate item parameters and standard errors (SEs) are crucial for many multidimensional item response theory (MIRT) applications. A recent study proposed the Gaussian Variational Expectation Maximization (GVEM) algorithm to improve computational efficiency and estimation accuracy (Cho et al., 2021). However, the SE estimation procedure has yet to…
Descriptors: Error of Measurement, Models, Evaluation Methods, Item Analysis
Martijn Schoenmakers; Jesper Tijmstra; Jeroen Vermunt; Maria Bolsinova – Educational and Psychological Measurement, 2024
Extreme response style (ERS), the tendency of participants to select extreme item categories regardless of the item content, has frequently been found to decrease the validity of Likert-type questionnaire results. For this reason, various item response theory (IRT) models have been proposed to model ERS and correct for it. Comparisons of these…
Descriptors: Item Response Theory, Response Style (Tests), Models, Likert Scales
Zsuzsa Bakk – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A standard assumption of latent class (LC) analysis is conditional independence, that is the items of the LC are independent of the covariates given the LCs. Several approaches have been proposed for identifying violations of this assumption. The recently proposed likelihood ratio approach is compared to residual statistics (bivariate residuals…
Descriptors: Goodness of Fit, Error of Measurement, Comparative Analysis, Models
Sweeney, Sandra M.; Sinharay, Sandip; Johnson, Matthew S.; Steinhauer, Eric W. – Educational Measurement: Issues and Practice, 2022
The focus of this paper is on the empirical relationship between item difficulty and item discrimination. Two studies--an empirical investigation and a simulation study--were conducted to examine the association between item difficulty and item discrimination under classical test theory and item response theory (IRT), and the effects of the…
Descriptors: Correlation, Item Response Theory, Item Analysis, Difficulty Level
Hoang V. Nguyen; Niels G. Waller – Educational and Psychological Measurement, 2024
We conducted an extensive Monte Carlo study of factor-rotation local solutions (LS) in multidimensional, two-parameter logistic (M2PL) item response models. In this study, we simulated more than 19,200 data sets that were drawn from 96 model conditions and performed more than 7.6 million rotations to examine the influence of (a) slope parameter…
Descriptors: Monte Carlo Methods, Item Response Theory, Correlation, Error of Measurement
Justin L. Kern – Journal of Educational and Behavioral Statistics, 2024
Given the frequent presence of slipping and guessing in item responses, models for the inclusion of their effects are highly important. Unfortunately, the most common model for their inclusion, the four-parameter item response theory model, potentially has severe deficiencies related to its possible unidentifiability. With this issue in mind, the…
Descriptors: Item Response Theory, Models, Bayesian Statistics, Generalization
van der Linden, Wim J.; Belov, Dmitry I. – Journal of Educational Measurement, 2023
A test of item compromise is presented which combines the test takers' responses and response times (RTs) into a statistic defined as the number of correct responses on the item for test takers with RTs flagged as suspicious. The test has null and alternative distributions belonging to the well-known family of compound binomial distributions, is…
Descriptors: Item Response Theory, Reaction Time, Test Items, Item Analysis
Sen, Sedat; Cohen, Allan S. – Educational and Psychological Measurement, 2023
The purpose of this study was to examine the effects of different data conditions on item parameter recovery and classification accuracy of three dichotomous mixture item response theory (IRT) models: the Mix1PL, Mix2PL, and Mix3PL. Manipulated factors in the simulation included the sample size (11 different sample sizes from 100 to 5000), test…
Descriptors: Sample Size, Item Response Theory, Accuracy, Classification
Xiao, Yue; Veldkamp, Bernard; Liu, Hongyun – Educational Measurement: Issues and Practice, 2022
The action sequences of respondents in problem-solving tasks reflect rich and detailed information about their performance, including differences in problem-solving ability, even if item scores are equal. It is therefore not sufficient to infer individual problem-solving skills based solely on item scores. This study is a preliminary attempt to…
Descriptors: Problem Solving, Item Response Theory, Scores, Item Analysis
Cum, Sait – International Journal of Assessment Tools in Education, 2021
In this study, it was claimed that ROC analysis, which is used to determine to what extent medical diagnosis tests can be differentiated between patients and non-patients, can also be used to examine the discrimination of binary scored items in cognitive tests. In order to obtain various evidence for this claim, the 2x2 contingency table used in…
Descriptors: Test Items, Item Analysis, Discriminant Analysis, Item Response Theory