That concern has nothing to do with centering variables before including them in a model.
Your multiple significance testing strategy is not based on statistical principles and will distort all inferences you obtain from the "final" model. Frank stamkiral wrote: > > variables were centered (except DV), because in social sciences zero is > rarely a meaningful point on a scale (Cohen, Cohen, West, Aiken, 2006). > for example in percieved social support questionnaire there is no value as > zero. It is a Likert Type questionnaire and on questionnaire 1= strongly > yes.....7= strongly no. So Aiken and West (1991), suggested to centered > predictors and moderators to appoint zero a meaningful value to count in > regression equation. also multilevel steps were run to avoid > multicollinearity. according to results .05 were accepted as significant > (in the coefficient table) and slope test were done for interactions. > for plottin slopes unstandardised regression coefficient were used. > ----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/multiple-moderated-regression-steps-tp3637807p3638669.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.