Greetings. I would adjust approach to calculate standardized estimates for each imputed set. Then summarize them . The way you are doing it here implies that standardization concept applies to model list, which seems doubtful. The empirical std. dev. of the variables differs among imputed data sets, after all. I suppose I mean to say lm.beta is not intended to receive a list of regressions. Put standardization in the with() work done on each imputed set. I suspect it is as easy as putting lm.beta in there. If there is trouble, I have a standardize function in the rockchalk package. Unlike lm.beta, it actually standardizes variables and runs regression. lm.beta resales coefficients instead. Paul Johnson University of Kansas On Wed, Sep 26, 2018, 5:03 AM CHATTON Anne via R-help <r-help at r-project.org> wrote:
Dear all, I am having problems in obtaining standardized betas on a multiply-imputed data set. Here are the codes I used : imp = mice(data, 5, maxit=10, seed=42, print=FALSE) FitImp <- with(imp,lm(y ~ x1 + x2 + x3)) Up to here everything is fine. But when I ask for the standardized coefficients of the multiply-imputed regressions using this command : sdBeta <- lm.beta(FitImp) I get the following error message: Error in b * sx : argument non num?rique pour un op?rateur binaire Can anyone help me with this please? Anne
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