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Showing 1 to 15 of 323 results Save | Export
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Kim, Nana; Bolt, Daniel M. – Educational and Psychological Measurement, 2021
This paper presents a mixture item response tree (IRTree) model for extreme response style. Unlike traditional applications of single IRTree models, a mixture approach provides a way of representing the mixture of respondents following different underlying response processes (between individuals), as well as the uncertainty present at the…
Descriptors: Item Response Theory, Response Style (Tests), Models, Test Items
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Spratto, Elisabeth M.; Leventhal, Brian C.; Bandalos, Deborah L. – Educational and Psychological Measurement, 2021
In this study, we examined the results and interpretations produced from two different IRTree models--one using paths consisting of only dichotomous decisions, and one using paths consisting of both dichotomous and polytomous decisions. We used data from two versions of an impulsivity measure. In the first version, all the response options had…
Descriptors: Comparative Analysis, Item Response Theory, Decision Making, Data Analysis
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Thomas, Michael L.; Brown, Gregory G.; Patt, Virginie M.; Duffy, John R. – Educational and Psychological Measurement, 2021
The adaptation of experimental cognitive tasks into measures that can be used to quantify neurocognitive outcomes in translational studies and clinical trials has become a key component of the strategy to address psychiatric and neurological disorders. Unfortunately, while most experimental cognitive tests have strong theoretical bases, they can…
Descriptors: Adaptive Testing, Computer Assisted Testing, Cognitive Tests, Psychopathology
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Park, Sung Eun; Ahn, Soyeon; Zopluoglu, Cengiz – Educational and Psychological Measurement, 2021
This study presents a new approach to synthesizing differential item functioning (DIF) effect size: First, using correlation matrices from each study, we perform a multigroup confirmatory factor analysis (MGCFA) that examines measurement invariance of a test item between two subgroups (i.e., focal and reference groups). Then we synthesize, across…
Descriptors: Item Analysis, Effect Size, Difficulty Level, Monte Carlo Methods
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Lenhard, Wolfgang; Lenhard, Alexandra – Educational and Psychological Measurement, 2021
The interpretation of psychometric test results is usually based on norm scores. We compared semiparametric continuous norming (SPCN) with conventional norming methods by simulating results for test scales with different item numbers and difficulties via an item response theory approach. Subsequently, we modeled the norm scores based on random…
Descriptors: Test Norms, Scores, Regression (Statistics), Test Items
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Schulte, Niklas; Holling, Heinz; Bürkner, Paul-Christian – Educational and Psychological Measurement, 2021
Forced-choice questionnaires can prevent faking and other response biases typically associated with rating scales. However, the derived trait scores are often unreliable and ipsative, making interindividual comparisons in high-stakes situations impossible. Several studies suggest that these problems vanish if the number of measured traits is high.…
Descriptors: Questionnaires, Measurement Techniques, Test Format, Scoring
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Wind, Stefanie A.; Schumacker, Randall E. – Educational and Psychological Measurement, 2021
Researchers frequently use Rasch models to analyze survey responses because these models provide accurate parameter estimates for items and examinees when there are missing data. However, researchers have not fully considered how missing data affect the accuracy of dimensionality assessment in Rasch analyses such as principal components analysis…
Descriptors: Item Response Theory, Data, Factor Analysis, Accuracy
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Dimitrov, Dimiter M.; Atanasov, Dimitar V. – Educational and Psychological Measurement, 2021
This study presents a latent (item response theory--like) framework of a recently developed classical approach to test scoring, equating, and item analysis, referred to as "D"-scoring method. Specifically, (a) person and item parameters are estimated under an item response function model on the "D"-scale (from 0 to 1) using…
Descriptors: Scoring, Equated Scores, Item Analysis, Item Response Theory
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Rios, Joseph A.; Soland, James – Educational and Psychological Measurement, 2021
As low-stakes testing contexts increase, low test-taking effort may serve as a serious validity threat. One common solution to this problem is to identify noneffortful responses and treat them as missing during parameter estimation via the effort-moderated item response theory (EM-IRT) model. Although this model has been shown to outperform…
Descriptors: Computation, Accuracy, Item Response Theory, Response Style (Tests)
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Man, Kaiwen; Harring, Jeffrey R. – Educational and Psychological Measurement, 2021
Many approaches have been proposed to jointly analyze item responses and response times to understand behavioral differences between normally and aberrantly behaved test-takers. Biometric information, such as data from eye trackers, can be used to better identify these deviant testing behaviors in addition to more conventional data types. Given…
Descriptors: Cheating, Item Response Theory, Reaction Time, Eye Movements
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Su, Shiyang; Wang, Chun; Weiss, David J. – Educational and Psychological Measurement, 2021
S-X[superscript 2] is a popular item fit index that is available in commercial software packages such as "flex"MIRT. However, no research has systematically examined the performance of S-X[superscript 2] for detecting item misfit within the context of the multidimensional graded response model (MGRM). The primary goal of this study was…
Descriptors: Statistics, Goodness of Fit, Test Items, Models
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Ames, Allison J.; Myers, Aaron J. – Educational and Psychological Measurement, 2021
Contamination of responses due to extreme and midpoint response style can confound the interpretation of scores, threatening the validity of inferences made from survey responses. This study incorporated person-level covariates in the multidimensional item response tree model to explain heterogeneity in response style. We include an empirical…
Descriptors: Response Style (Tests), Item Response Theory, Longitudinal Studies, Adolescents
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Mansolf, Maxwell; Vreeker, Annabel; Reise, Steven P.; Freimer, Nelson B.; Glahn, David C.; Gur, Raquel E.; Moore, Tyler M.; Pato, Carlos N.; Pato, Michele T.; Palotie, Aarno; Holm, Minna; Suvisaari, Jaana; Partonen, Timo; Kieseppä, Tuula; Paunio, Tiina; Boks, Marco; Kahn, René; Ophoff, Roel A.; Bearden, Carrie E.; Loohuis, Loes Olde; Teshiba, Terri; deGeorge, Daniella; Bilder, Robert M. – Educational and Psychological Measurement, 2020
Large-scale studies spanning diverse project sites, populations, languages, and measurements are increasingly important to relate psychological to biological variables. National and international consortia already are collecting and executing mega-analyses on aggregated data from individuals, with different measures on each person. In this…
Descriptors: Item Response Theory, Data Analysis, Measurement, Validity
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Jang, Yoonsun; Cohen, Allan S. – Educational and Psychological Measurement, 2020
A nonconverged Markov chain can potentially lead to invalid inferences about model parameters. The purpose of this study was to assess the effect of a nonconverged Markov chain on the estimation of parameters for mixture item response theory models using a Markov chain Monte Carlo algorithm. A simulation study was conducted to investigate the…
Descriptors: Markov Processes, Item Response Theory, Accuracy, Inferences
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Yang, Lihong; Reckase, Mark D. – Educational and Psychological Measurement, 2020
The present study extended the "p"-optimality method to the multistage computerized adaptive test (MST) context in developing optimal item pools to support different MST panel designs under different test configurations. Using the Rasch model, simulated optimal item pools were generated with and without practical constraints of exposure…
Descriptors: Item Banks, Adaptive Testing, Computer Assisted Testing, Item Response Theory
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