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From | Aggie Chidlow <mojamalarybka@googlemail.com> |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: st: Pseudo R2 after "mi estimate:logit" |
Date | Mon, 14 Mar 2011 21:12:54 +0000 |
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? > > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/