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Bodner, Todd E. – Journal of Educational and Behavioral Statistics, 2016
This article revisits how the end points of plotted line segments should be selected when graphing interactions involving a continuous target predictor variable. Under the standard approach, end points are chosen at ±1 or 2 standard deviations from the target predictor mean. However, when the target predictor and moderator are correlated or the…
Descriptors: Graphs, Multiple Regression Analysis, Predictor Variables, Correlation
Leckie, George; Pillinger, Rebecca; Jones, Kelvyn; Goldstein, Harvey – Journal of Educational and Behavioral Statistics, 2012
The traditional approach to measuring segregation is based upon descriptive, non-model-based indices. A recently proposed alternative is multilevel modeling. The authors further develop the argument for a multilevel modeling approach by first describing and expanding upon its notable advantages, which include an ability to model segregation at a…
Descriptors: Statistical Analysis, Models, Simulation, Measurement Techniques
Aloe, Ariel M.; Becker, Betsy Jane – Journal of Educational and Behavioral Statistics, 2012
A new effect size representing the predictive power of an independent variable from a multiple regression model is presented. The index, denoted as r[subscript sp], is the semipartial correlation of the predictor with the outcome of interest. This effect size can be computed when multiple predictor variables are included in the regression model…
Descriptors: Meta Analysis, Effect Size, Multiple Regression Analysis, Models

Rindskopf, David – Journal of Educational and Behavioral Statistics, 2002
Asserts that, in principle, an analyst should be satisfied with infinite estimates slope in logistic regression because it indicates that a predictor is perfect. Using simple approaches, hypothesis tests may be performed and confidence intervals calculated even when a slope is infinite. Some functions of parameters that are infinite are still…
Descriptors: Estimation (Mathematics), Predictor Variables, Regression (Statistics)
Bauer, Daniel J. – Journal of Educational and Behavioral Statistics, 2003
Multilevel linear models (MLMs) provide a powerful framework for analyzing data collected at nested or non-nested levels, such as students within classrooms. The current article draws on recent analytical and software advances to demonstrate that a broad class of MLMs may be estimated as structural equation models (SEMs). Moreover, within the SEM…
Descriptors: Structural Equation Models, Data Analysis, Computer Software, Evaluation Methods