Relative power of moderated multiple regression and the comparison of subgroup correlation coefficients for detecting moderating effects.

Abstract

A Monte Carlo simulation assessed the relative power of 2 techniques that are commonly used to test for moderating effects. The authors drew 500 samples from simulation-based populations for each of 81 conditions in a design that varied sample size, the reliabilities of 2 predictor variables (1 of which was the moderator variable), and the magnitude of the moderating effect. They tested the null hypothesis of no interaction effect by using moderated multiple regression (MMR). They then successively polychotomized each sample into 2, 3, 4, 6, and 8 subgroups and tested the equality of the subgroup-based correlation coefficients (SCC). Results showed MMR to be more powerful than the SCC strategy for virtually all of the 81 conditions.

Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementations

“…But this method does not properly represent how the focal predictor variable's effect varies as a function of the moderator, especially when additional variables in the model are used as statistical controls. For details about the problems with this method-a method we do not recommend-see Newsom, Prigerson, Schulz, and Reynolds (2003) and Stone-Romero and Anderson (1994).Fortunately, there are more rigorous and appropriate methods for probing interactions in linear models, two of which we will describe in this article. The first method we discuss, the pick-a-point approach, is one of the more commonly used.…”

“…But this method does not properly represent how the focal predictor variable's effect varies as a function of the moderator, especially when additional variables in the model are used as statistical controls. For details about the problems with this method-a method we do not recommend-see Newsom, Prigerson, Schulz, and Reynolds (2003) and Stone-Romero and Anderson (1994).…”

Habit and information use in travel mode choices

“…Such strategy is described as noncompensatory, and can be measured by testing whether the increment in R 2 is significant when the interactions among attributes are added to the regression model (cf. Stone-Romero and Anderson, 1994). In order to test whether accountability is related to such an increment in R 2, for each subject all first-order interactions among attributes were added to the original predictors (i.e., main effects) in the regression analysis.…”

Interaction between the Process Used to Introduce Change and the Personality of Organizational Members: An International Test

“…The purpose of this study, as identified previously, is to examine the relationships between individuals' perceptions of the change process, their personality traits, and their readiness for change. Consistent with previous research (Baron & Kenny, 1986;Ciarrochi, Deane, & Anderson, 2002;Daly, 1995;Judge, 1993;Newton & Keenan, 1990;Salas & Jentsch, 1996;Smith-Jentsch, Payne, Sher, & Lee, 2003;Stone-Romero & Anderson, 1994;Vakola, Tsaousis, & Nikolaou, 2004;Wanberg & Banas, 2000) the use of moderated multiple regression to conduct the statistical analysis was chosen.…”