[R] Problems to obtain standardized betas in multiply-imputed data
p@uljohn32 @ending from gm@il@com
Fri Oct 5 10:46:50 CEST 2018
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,
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.
University of Kansas
On Wed, Sep 26, 2018, 5:03 AM CHATTON Anne via R-help <r-help using r-project.org>
> 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 numérique pour un opérateur binaire
> Can anyone help me with this please?
> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> PLEASE do read the posting guide
> and provide commented, minimal, self-contained, reproducible code.
[[alternative HTML version deleted]]
More information about the R-help