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Isaac M. Opper – Annenberg Institute for School Reform at Brown University, 2021
Researchers often include covariates when they analyze the results of randomized controlled trials (RCTs), valuing the increased precision of the estimates over the potential of inducing small-sample bias when doing so. In this paper, we develop a sufficient condition which ensures that the inclusion of covariates does not cause small-sample bias…
Descriptors: Randomized Controlled Trials, Sample Size, Statistical Bias, Artificial Intelligence
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Tutz, Gerhard; Berger, Moritz – Journal of Educational and Behavioral Statistics, 2016
Heterogeneity in response styles can affect the conclusions drawn from rating scale data. In particular, biased estimates can be expected if one ignores a tendency to middle categories or to extreme categories. An adjacent categories model is proposed that simultaneously models the content-related effects and the heterogeneity in response styles.…
Descriptors: Response Style (Tests), Rating Scales, Data Interpretation, Statistical Bias
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McNeish, Daniel M. – Journal of Educational and Behavioral Statistics, 2016
Mixed-effects models (MEMs) and latent growth models (LGMs) are often considered interchangeable save the discipline-specific nomenclature. Software implementations of these models, however, are not interchangeable, particularly with small sample sizes. Restricted maximum likelihood estimation that mitigates small sample bias in MEMs has not been…
Descriptors: Models, Statistical Analysis, Hierarchical Linear Modeling, Sample Size
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Preston, Kathleen Suzanne Johnson; Reise, Steven Paul – Educational and Psychological Measurement, 2014
The nominal response model (NRM), a much understudied polytomous item response theory (IRT) model, provides researchers the unique opportunity to evaluate within-item category distinctions. Polytomous IRT models, such as the NRM, are frequently applied to psychological assessments representing constructs that are unlikely to be normally…
Descriptors: Item Response Theory, Computation, Models, Accuracy
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Nandakumar, Ratna; Yu, Feng; Zhang, Yanwei – Applied Psychological Measurement, 2011
DETECT is a nonparametric methodology to identify the dimensional structure underlying test data. The associated DETECT index, "D[subscript max]," denotes the degree of multidimensionality in data. Conditional covariances (CCOV) are the building blocks of this index. In specifying population CCOVs, the latent test composite [theta][subscript TT]…
Descriptors: Nonparametric Statistics, Statistical Analysis, Tests, Data
OECD Publishing, 2014
The Programme for International Assessment of Adult Competencies (PIAAC) will establish technical standards and guidelines to ensure that the survey design and implementation processes of PIAAC yield high-quality and internationally comparable data. This document provides a revised version of the technical standards and guidelines originally…
Descriptors: Adults, International Assessment, Adult Literacy, Competence