Journal•ISSN: 1076-9986
Journal of Educational and Behavioral Statistics
SAGE Publishing
About: Journal of Educational and Behavioral Statistics is an academic journal published by SAGE Publishing. The journal publishes majorly in the area(s): Item response theory & Sample size determination. It has an ISSN identifier of 1076-9986. Over the lifetime, 1197 publications have been published receiving 71889 citations.
Topics: Item response theory, Sample size determination, Bayesian statistics, Regression analysis, Multilevel model
Papers published on a yearly basis
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TL;DR: The authors provides an overview of methods used to probe interaction effects and describes a unified collection offreely available online resources that researchers can use to obtain significance tests and confidence bands for simple slopes across the range of the moderator in the MLR, HLM, and LCA contexts.
Abstract: Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests andplotting the conditional relations is often a tedious and error-prone task. This article provides an overview of methods used to probe interaction effects and describes a unified collection offreely available online resources that researchers can use to obtain significance testsforsimple slopes, compute regions of significance, and obtain confidence bands for simple slopes across the range of the moderator in the MLR, HLM, and LCA contexts. Plotting capabilities are also provided.
4,505 citations
TL;DR: In this article, the effect size estimator of Glass's estimator, the sample mean difference divided by the sample standard deviation, is studied in the context of an explicit statistical model.
Abstract: Glass's estimator of effect size, the sample mean difference divided by the sample standard deviation, is studied in the context of an explicit statistical model. The exact distribution of Glass's estimator is obtained and the estimator is shown to have a small sample bias. The minimum variance unbiased estimator is obtained and shown to have uniformly smaller variance than Glass's (biased) estimator. Measurement error is shown to attenuate estimates of effect size and a correction is given. The effects of measurement invalidity are discussed. Expressions for weights that yield the most precise weighted estimate of effect size are also derived.
3,880 citations
TL;DR: This paper is written as a step-by-step tutorial that shows how to fit the two most common multilevel models: (a) school effects models, designed for data on individuals nested within naturally occurring hierarchies (e.g., students within classes); and (b) individual growth models,designed for exploring longitudinal data (on individuals) over time.
Abstract: SAS PROC MIXED is a flexible program suitable for fitting multilevel models, hierarchical linear models, and individual growth models. Its position as an integrated program within the SAS statistic...
2,903 citations
TL;DR: The previous editions of this book, written by the first two authors, Jacob and Patricia Cohen, became essential reference tools for many social scientists who needed a solid grounding in statistical methodology.
Abstract: The previous editions of this book, written by the first two authors, Jacob and Patricia Cohen, became essential reference tools for many social scientists who needed a solid grounding in statistical methodology. It was first published in 1975, with an intention to provide a foundation in the regression framework for the practical researcher. The second edition (1983) focused on causality and analysis of variance and covariance. The third edition is even more extensive, containing extra topics that have evolved over the last 20 years, and has extensions of earlier chapters. It remains as vital as ever.
2,224 citations
1,995 citations