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Showing 1 to 15 of 415 results Save | Export
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Wang, Yan; Kim, Eunsook; Yi, Zhiyao – Educational and Psychological Measurement, 2022
Latent profile analysis (LPA) identifies heterogeneous subgroups based on continuous indicators that represent different dimensions. It is a common practice to measure each dimension using items, create composite or factor scores for each dimension, and use these scores as indicators of profiles in LPA. In this case, measurement models for…
Descriptors: Robustness (Statistics), Profiles, Statistical Analysis, Classification
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Liu, Ren; Liu, Haiyan; Shi, Dexin; Jiang, Zhehan – Educational and Psychological Measurement, 2022
Assessments with a large amount of small, similar, or often repetitive tasks are being used in educational, neurocognitive, and psychological contexts. For example, respondents are asked to recognize numbers or letters from a large pool of those and the number of correct answers is a count variable. In 1960, George Rasch developed the Rasch…
Descriptors: Classification, Models, Statistical Distributions, Scores
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van Dijk, Wilhelmina; Schatschneider, Christopher; Al Otaiba, Stephanie; Hart, Sara A. – Educational and Psychological Measurement, 2022
Complex research questions often need large samples to obtain accurate estimates of parameters and adequate power. Combining extant data sets into a large, pooled data set is one way this can be accomplished without expending resources. Measurement invariance (MI) modeling is an established approach to ensure participant scores are on the same…
Descriptors: Sample Size, Data Analysis, Goodness of Fit, Measurement
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Ames, Allison J. – Educational and Psychological Measurement, 2022
Individual response style behaviors, unrelated to the latent trait of interest, may influence responses to ordinal survey items. Response style can introduce bias in the total score with respect to the trait of interest, threatening valid interpretation of scores. Despite claims of response style stability across scales, there has been little…
Descriptors: Response Style (Tests), Individual Differences, Scores, Test Items
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Brennan, Robert L.; Kim, Stella Y.; Lee, Won-Chan – Educational and Psychological Measurement, 2022
This article extends multivariate generalizability theory (MGT) to tests with different random-effects designs for each level of a fixed facet. There are numerous situations in which the design of a test and the resulting data structure are not definable by a single design. One example is mixed-format tests that are composed of multiple-choice and…
Descriptors: Multivariate Analysis, Generalizability Theory, Multiple Choice Tests, Test Construction
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Agley, Jon; Tidd, David; Jun, Mikyoung; Eldridge, Lori; Xiao, Yunyu; Sussman, Steve; Jayawardene, Wasantha; Agley, Daniel; Gassman, Ruth; Dickinson, Stephanie L. – Educational and Psychological Measurement, 2021
Prospective longitudinal data collection is an important way for researchers and evaluators to assess change. In school-based settings, for low-risk and/or likely-beneficial interventions or surveys, data quality and ethical standards are both arguably stronger when using a waiver of parental consent--but doing so often requires the use of…
Descriptors: Data Analysis, Longitudinal Studies, Data Collection, Intervention
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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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Ferrando, Pere J.; Lorenzo-Seva, Urbano – Educational and Psychological Measurement, 2021
Unit-weight sum scores (UWSSs) are routinely used as estimates of factor scores on the basis of solutions obtained with the nonlinear exploratory factor analysis (EFA) model for ordered-categorical responses. Theoretically, this practice results in a loss of information and accuracy, and is expected to lead to biased estimates. However, the…
Descriptors: Scores, Factor Analysis, Automation, Fidelity
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Roozenbeek, Jon; Maertens, Rakoen; McClanahan, William; van der Linden, Sander – Educational and Psychological Measurement, 2021
Online misinformation is a pervasive global problem. In response, psychologists have recently explored the theory of psychological inoculation: If people are preemptively exposed to a weakened version of a misinformation technique, they can build up cognitive resistance. This study addresses two unanswered methodological questions about a widely…
Descriptors: Games, Intervention, Scores, Pretests Posttests
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Nam, Yeji; Hong, Sehee – Educational and Psychological Measurement, 2021
This study investigated the extent to which class-specific parameter estimates are biased by the within-class normality assumption in nonnormal growth mixture modeling (GMM). Monte Carlo simulations for nonnormal GMM were conducted to analyze and compare two strategies for obtaining unbiased parameter estimates: relaxing the within-class normality…
Descriptors: Probability, Models, Statistical Analysis, Statistical Distributions
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Chen, Michelle Y.; Liu, Yan; Zumbo, Bruno D. – Educational and Psychological Measurement, 2020
This study introduces a novel differential item functioning (DIF) method based on propensity score matching that tackles two challenges in analyzing performance assessment data, that is, continuous task scores and lack of a reliable internal variable as a proxy for ability or aptitude. The proposed DIF method consists of two main stages. First,…
Descriptors: Probability, Scores, Evaluation Methods, Test Items
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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
Aytürk, Ezgi; Cham, Heining; Jennings, Patricia A.; Brown, Joshua L. – Educational and Psychological Measurement, 2020
Methods to handle ordered-categorical indicators in latent variable interactions have been developed, yet they have not been widely applied. This article compares the performance of two popular latent variable interaction modeling approaches in handling ordered-categorical indicators: unconstrained product indicator (UPI) and latent moderated…
Descriptors: Evaluation Methods, Grade 3, Grade 4, Grade 5
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Yesiltas, Gonca; Paek, Insu – Educational and Psychological Measurement, 2020
A log-linear model (LLM) is a well-known statistical method to examine the relationship among categorical variables. This study investigated the performance of LLM in detecting differential item functioning (DIF) for polytomously scored items via simulations where various sample sizes, ability mean differences (impact), and DIF types were…
Descriptors: Simulation, Sample Size, Item Analysis, Scores
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Raymond, Mark R.; Jiang, Zhehan – Educational and Psychological Measurement, 2020
Conventional methods for evaluating the utility of subscores rely on traditional indices of reliability and on correlations among subscores. One limitation of correlational methods is that they do not explicitly consider variation in subtest means. An exception is an index of score profile reliability designated as [G], which quantifies the ratio…
Descriptors: Generalizability Theory, Multivariate Analysis, Scores, Reliability
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