I discovered the same kind of results with Multiple imputation in
ordinary GLM. I have reported it to SPSS but haven't received any
explanation yet.
Best,
Henrik
Quoting "Ginkel, Joost van" <
JGinkel@...>:
> I have tried the Multiple imputation procedure in PASW 17 for analyzing
> a data set with missing values. The procedure is quite user-friendly.
> However, when using the procedure I discovered some strange things about
> the pooled results in the output. The pooled significance tests from a
> regression model sometimes have p-values that are exactly equal to 1. I
> find it hard to believe that these results are correct since the
> p-values of the 5 imputed datasets vary around 0.20. I can imagine that
> SE's increase due to the extra uncertainty because of the missing data,
> but I can't imagine that this p-value increases exactly to one. Thus
> far, I have only seen this occur within the procedure Mixed models so I
> don't know if it occurs in other procedures as well. For people who want
> to see what I mean, I can send the data and the syntax file that
> generated these results, on request.
>
> Best regards,
>
> Joost van Ginkel
>
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************************************************************
Henrik Lolle
Department of Economics, Politics and Public Administration
Aalborg University
Fibigerstraede 1
9200 Aalborg
Phone: (+45) 99 40 81 84
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