Re: st: Pseudo R2 after "mi estimate:logit"

[Aggie Chidlow <mojamalarybka@googlemail.com>]

Thank you Nick.

My ".di mindouble()" is the same as yours.
Thank you for this... I use it follwoing the information I have read
regarding ineligible missing values.

I have just gen lnx = ln(x) and the results are better.

Would you mind telling me how do I know that  for example 30
imputations (M=30) is the adequate
number? I am asking because according to Rubin (1987) only 3-10
imputations may be needed?

On Mon, Mar 14, 2011 at 8:38 PM, Nick Cox <n.j.cox@durham.ac.uk> wrote:
> Not at all the question you asked, but my eye fell on
>
> cond(x==0, mindouble(), log(x3))
>
> This transformation I guess, arises because you feel you should take logs, but there are zeros in your data. But what is mindouble()? In my Stata
>
> . di mindouble()
> -8.99e+307
>
> It is negative and massive! Clearly, I don't know what other values you have in your data, but even if they are of the order of 1e6 or 1e9, that introduced value will still be relatively much larger.
>
> So, if there really are zeros, it looks as if you intend to introduce massive outliers into your data.
>
> To be sure, log 0 is indeterminate and logarithms of very small numbers << 1 are large and negative, but it is hard to believe that this way of dealing won't dominate that variable and very likely the whole model results.
>
> All that said, unless you have elsewhere
>
> . set type double
>
> you are generating this variable as a -float-, but a -float- can't hold -mindouble()- and the result would just be missing in those observations.
>
> Nick
> n.j.cox@durham.ac.uk
>
> Aggie Chidlow
>
> My do-file is:
>
> mi set mlong
> mi query
> mi describe
> mi misstable sum
> generate lnx = cond(x==0, mindouble(), log(x3))
> mi register imputed lnx
> set seed 29390
> mi describe
> mi impute mvn lnx = x1 x2 x3 x4 x5 x6 x7,add(30)
> mi estimate: logit x1 x2 x3 x4 x5 x6 x7 lnx
> mi xeq 0 1 30: logit x1 x2 x3 x4 x5 x6 x7 lnx
>
> For example from "mi xeq 30:logit x1 x2 x3 x4 x5 x6 x7 lnx" I can see
> Wald test.However, from "mi estimate: logit x1 x2 x3 x4 x5 x6 x7 lnx"
> I can only see F test. So, how can I get Wald test from "mi estimate:
> logit"?
>
> Further, how do I know that 30 imputations (M=30) is the adequate
> number? I am asking because according to Rubin (1987) only 3-10
> imputations may be needed?
>
>
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