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Fwd: st: Convergence never achieved with MI impute chained


From   Lena Lindbjerg Sperling <lenalindbjergsperling@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Fwd: st: Convergence never achieved with MI impute chained
Date   Thu, 21 Jun 2012 13:46:06 +0200

> 
> Thank you for your answer! 
> 
> It does seem though that all occupations are represented in both private and public sectors. 
> And I also have another data set where I only impute educational level, industry (ISIC 3 category) and wage and I still get not convergence, even though that's just one mlogit, one ologit and one pmm...so that doesn't seem to be the problem.
> 
> I got a result out for the mi xeq 0: mlogit for industry however and it looks like this:
> ->	mlogit	industry				
Iteration	0:00	log	likelihood	=	-4875.9554	
Iteration	1:00	log	likelihood	=	-4875.9554	
Multinomial	logistic	regression	Number	of	obs	=
LR	chi2(0)	=	0			
Prob	>	chi2	=	.		
Log	likelihood	=	-4875.9554	Pseudo	R2	=
industry	Coef.	Std.	Err.	z	P>z	[95%
Agriculture__Hunting__etc_	(base	outcome)				
Mining						
_cons	-4.982464	0.2896632	-17.2	0	-5.550194	-4.414735
Manufacturing						
_cons	-2.671581	0.0939994	-28.42	0	-2.855816	-2.487345
Public_services						
_cons	-3.42432	0.134593	-25.44	0	-3.688117	-3.160522
Construction						
_cons	-3.204691	0.1210617	-26.47	0	-3.441968	-2.967415
Retail__Hotels						
_cons	-1.714798	0.0612048	-28.02	0	-1.834758	-1.594839
Transport_and_telecomnunications				
_cons	-4.759321	0.2593031	-18.35	0	-5.267546	-4.251096
Finance_and_business_serv_					
_cons	-6.368759	0.5778449	-11.02	0	-7.501314	-5.236204
Communal_services					
_cons	-0.830113	0.0433825	-19.13	0	-0.9151412	-0.7450848
Others_not_well_specified					
_cons	-1.753638	0.0622235	-28.18	0	-1.875594	-1.631683
> 
> Should I use something else to impute this? It runs from 1 to 10 so maybe ordered is better? I get convergence if I use ordered logit for industry and occupation. They really shouldn't be ordered, but how important is that choice?
> 
> 
> I can get results out if I use mvn, but is that a very bad idea? Seems like the literature disagrees quite a bit on how severe it is to assume normality?
> 
> Best,
> Lena
> 
> Den Jun 21, 2012 kl. 10:48 AM skrev Maarten Buis:
> 
>> On Thu, Jun 21, 2012 at 10:15 AM, Lena Lindbjerg Sperling wrote:
>>> I just looked at the mail again, and the data is not as bad as it looks, as I'm only imputing on the employed population (lstatus==1) and when we only look at them mi describe shows:
>>> mi describe
>>> 
>>> Style:  wide
>>>         last mi update 21jun2012 10:03:51, 18 seconds ago
>>> 
>>> Obs.:   complete        2,702
>>>         incomplete        912  (M = 0 imputations)
>>>         ---------------------
>>>         total           3,614
>>> 
>>> Vars.:  imputed:  7; occup(126) ocusec(144) whours(167) edulevel(171) ocu(228) industry(204) mwage(598)
>> 
>> Just looking at the variable names I suspect that this is an extremely
>> hard model to estimate. How many categories do the variables occup,
>> ocusec, ocu, and industry have? Are there combinations of three or
>> less of these that for some observations perfectly predict one or more
>> remaining variables? For example, if we know that someone is a mayor
>> than we also know that (s)he is working in the public sector.
>> 
>> <snip>
>>> Iteration 14:  log pseudolikelihood = -2454486.7  (not concave)
>>> Not completely sure what this means. Can you see where things are wrong from this?
>> 
>> It means that this sub-model did not converge, probably because of the
>> problems indicated above.
>> 
>>> When I use -mi xeq 0: mlogit - the result is:
>>> m=0 data:
>>> -> mlogit
>>> last estimates not found
>>> r(301);
>>> 
>>> But I thought it was the observed data...which should be there?
>> 
>> What you asked for was for Stata to replay the last -mlogit- command,
>> and it replied that the last command wasn't -mlogit-. You probably
>> pressed break before the model finished estimating, which makes sense
>> if it did not converge.
>> 
>> Hope this helps,
>> Maarten
>> 
>> --------------------------
>> Maarten L. Buis
>> Institut fuer Soziologie
>> Universitaet Tuebingen
>> Wilhelmstrasse 36
>> 72074 Tuebingen
>> Germany
>> 
>> 
>> http://www.maartenbuis.nl
>> --------------------------
>> 
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> 


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