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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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Chan, Wendy – Journal of Research on Educational Effectiveness, 2022
Over the past decade, statisticians have developed methods to improve generalizations from nonrandom samples using propensity score methods. While these methods contribute to generalization research, their effectiveness is limited by small sample sizes. Small area estimation is a class of model-based methods that address the imprecision due to…
Descriptors: Generalization, Probability, Sample Size, Statistical Analysis
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Weese, James D.; Turner, Ronna C.; Ames, Allison; Crawford, Brandon; Liang, Xinya – Educational and Psychological Measurement, 2022
A simulation study was conducted to investigate the heuristics of the SIBTEST procedure and how it compares with ETS classification guidelines used with the Mantel-Haenszel procedure. Prior heuristics have been used for nearly 25 years, but they are based on a simulation study that was restricted due to computer limitations and that modeled item…
Descriptors: Test Bias, Heuristics, Classification, Statistical Analysis
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Su, Kun; Henson, Robert A. – Journal of Educational and Behavioral Statistics, 2023
This article provides a process to carefully evaluate the suitability of a content domain for which diagnostic classification models (DCMs) could be applicable and then optimized steps for constructing a test blueprint for applying DCMs and a real-life example illustrating this process. The content domains were carefully evaluated using a set of…
Descriptors: Classification, Models, Science Tests, Physics
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Weese, James D.; Turner, Ronna C.; Liang, Xinya; Ames, Allison; Crawford, Brandon – Educational and Psychological Measurement, 2023
A study was conducted to implement the use of a standardized effect size and corresponding classification guidelines for polytomous data with the POLYSIBTEST procedure and compare those guidelines with prior recommendations. Two simulation studies were included. The first identifies new unstandardized test heuristics for classifying moderate and…
Descriptors: Effect Size, Classification, Guidelines, Statistical Analysis
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Cassiday, Kristina R.; Cho, Youngmi; Harring, Jeffrey R. – Educational and Psychological Measurement, 2021
Simulation studies involving mixture models inevitably aggregate parameter estimates and other output across numerous replications. A primary issue that arises in these methodological investigations is label switching. The current study compares several label switching corrections that are commonly used when dealing with mixture models. A growth…
Descriptors: Probability, Models, Simulation, Mathematics
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V. N. Vimal Rao; Jeffrey K. Bye; Sashank Varma – Cognitive Research: Principles and Implications, 2024
The 0.05 boundary within Null Hypothesis Statistical Testing (NHST) "has made a lot of people very angry and been widely regarded as a bad move" (to quote Douglas Adams). Here, we move past meta-scientific arguments and ask an empirical question: What is the psychological standing of the 0.05 boundary for statistical significance? We…
Descriptors: Psychological Patterns, Statistical Analysis, Testing, Statistical Significance
Wang, Chun; Lu, Jing – Journal of Educational and Behavioral Statistics, 2021
In cognitive diagnostic assessment, multiple fine-grained attributes are measured simultaneously. Attribute hierarchies are considered important structural features of cognitive diagnostic models (CDMs) that provide useful information about the nature of attributes. Templin and Bradshaw first introduced a hierarchical diagnostic classification…
Descriptors: Cognitive Measurement, Models, Vertical Organization, Classification
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Yilmaz, Ismail – Educational Research and Reviews, 2020
When correlation between variables is not explicit, data can be collected by adapting the quantitative measurement tools in use for quantitative measurement of possibility, a nonlinear measurement. This adaptation is possible because measurement data can be evaluated more qualitatively using parameters for possibility. These can be defined as…
Descriptors: Correlation, Statistical Analysis, Qualitative Research, Classification
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Bashir, Rabia; Dunn, Adam G.; Surian, Didi – Research Synthesis Methods, 2021
Few data-driven approaches are available to estimate the risk of conclusion change in systematic review updates. We developed a rule-based approach to automatically extract information from reviews and updates to be used as features for modelling conclusion change risk. Rules were developed to extract relevant information from published Cochrane…
Descriptors: Literature Reviews, Data, Automation, Statistical Analysis
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Bonifay, Wes; Depaoli, Sarah – Prevention Science, 2023
Statistical analysis of categorical data often relies on multiway contingency tables; yet, as the number of categories and/or variables increases, the number of table cells with few (or zero) observations also increases. Unfortunately, sparse contingency tables invalidate the use of standard goodness-of-fit statistics. Limited-information fit…
Descriptors: Bayesian Statistics, Programming Languages, Psychopathology, Classification
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Grund, Simon; Lüdtke, Oliver; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2023
Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…
Descriptors: Educational Research, Data Analysis, Error of Measurement, Computation
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Robitzsch, Alexander – Journal of Intelligence, 2020
The last series of Raven's standard progressive matrices (SPM-LS) test was studied with respect to its psychometric properties in a series of recent papers. In this paper, the SPM-LS dataset is analyzed with regularized latent class models (RLCMs). For dichotomous item response data, an alternative estimation approach based on fused regularization…
Descriptors: Statistical Analysis, Classification, Intelligence Tests, Test Items
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Alahmadi, Sarah; Jones, Andrew T.; Barry, Carol L.; Ibáñez, Beatriz – Applied Measurement in Education, 2023
Rasch common-item equating is often used in high-stakes testing to maintain equivalent passing standards across test administrations. If unaddressed, item parameter drift poses a major threat to the accuracy of Rasch common-item equating. We compared the performance of well-established and newly developed drift detection methods in small and large…
Descriptors: Equated Scores, Item Response Theory, Sample Size, Test Items
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Rubio-Aparicio, María; López-López, José Antonio; Viechtbauer, Wolfgang; Marín-Martínez, Fulgencio; Botella, Juan; Sánchez-Meca, Julio – Journal of Experimental Education, 2020
Mixed-effects models can be used to examine the association between a categorical moderator and the magnitude of the effect size. Two approaches are available to estimate the residual between-studies variance, t[superscript 2][subscript res] --namely, separate estimation within each category of the moderator versus pooled estimation across all…
Descriptors: Meta Analysis, Effect Size, Computation, Classification
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