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Hi, I was wondering if the pvalues given for variances are the onetailed pvalues or are they really the twotailed pvalues as labeled? Thanks 


It is a twotailed test. There is a literature on testing variances against zero. See, for example, Stoel, R.D., Garre, F.G., Donal, C., and van den Wittenboer, G. (2006) On the likelihood ratio test in structural equation modeling when parameters are subject to boundary constraints. Psychological Methods,11, 439455. 

C. Lechner posted on Wednesday, May 15, 2013  6:57 am



Dear Linda and Bengt, I have a multilevel model involving a crosslevel interaction between a level1 predictor x and a level2 predictor w: %within% x_slope  y ON x; %between% y x_slope ON w; y WITH x_slope ; I noticed that the pvalue of the residual variance of the slope depends strongly on centering option. Specifically, if I center x, the residual variance of x_slope is n.s. However, if I do not center x, the residual variance is highly significant. How does this come about? Should x not be centered if it gets a random slope? Note: In a model without w, x_slope does have a significant level2 variance. Thanks in advance for clarification. 


I would check centering in the 2002 Raudenbush and Bryk book. 

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