TY - JOUR
T1 - Sample size determination for confidence intervals of interaction effects in moderated multiple regression with continuous predictor and moderator variables
AU - Shieh, Gwowen
PY - 2010/8/1
Y1 - 2010/8/1
N2 - Moderated multiple regression (MMR) has been widely employed to analyze the interaction or moderating effects in behavior and related disciplines of social science. Much of the methodological literature in the context of MMR concerns statistical power and sample size calculations of hypothesis tests for detecting moderator variables. Notably, interval estimation is a distinct and more informative alternative to significance testing for inference purposes. To facilitate the practice of reporting confidence intervals in MMR analyses, the present article presents two approaches to sample size determinations for precise interval estimation of interaction effects between continuous moderator and predictor variables. One approach provides the necessary sample size so that the designated interval for the least squares estimator of moderating effects attains the specified coverage probability. The other gives the sample size required to ensure, with a given tolerance probability, that a confidence interval of moderating effects with a desired confidence coefficient will be within a specified range. Numerical examples and simulation results are presented to illustrate the usefulness and advantages of the proposed methods that account for the embedded randomness and distributional characteristic of the moderator and predictor variables.
AB - Moderated multiple regression (MMR) has been widely employed to analyze the interaction or moderating effects in behavior and related disciplines of social science. Much of the methodological literature in the context of MMR concerns statistical power and sample size calculations of hypothesis tests for detecting moderator variables. Notably, interval estimation is a distinct and more informative alternative to significance testing for inference purposes. To facilitate the practice of reporting confidence intervals in MMR analyses, the present article presents two approaches to sample size determinations for precise interval estimation of interaction effects between continuous moderator and predictor variables. One approach provides the necessary sample size so that the designated interval for the least squares estimator of moderating effects attains the specified coverage probability. The other gives the sample size required to ensure, with a given tolerance probability, that a confidence interval of moderating effects with a desired confidence coefficient will be within a specified range. Numerical examples and simulation results are presented to illustrate the usefulness and advantages of the proposed methods that account for the embedded randomness and distributional characteristic of the moderator and predictor variables.
KW - Moderator variable
KW - coverage probability
KW - Interval estimation
KW - Sample size determination
KW - Random regression
UR - http://www.scopus.com/inward/record.url?scp=77957701206&partnerID=8YFLogxK
U2 - 10.3758/BRM.42.3.824
DO - 10.3758/BRM.42.3.824
M3 - Article
C2 - 20805605
AN - SCOPUS:77957701206
SN - 1554-351X
VL - 42
SP - 824
EP - 835
JO - Behavior Research Methods
JF - Behavior Research Methods
IS - 3
ER -