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From |
Lena Lindbjerg Sperling <[email protected]> |

To |
[email protected] |

Subject |
Re: st: Convergence never achieved with MI impute chained |

Date |
Fri, 22 Jun 2012 13:07:03 +0200 |

Thank you Maarten. I am in developing countries:-) And what we are trying to explore is the development in wages and movement of workers across sectors, so I can't really destroy the industry category as this is our final interest. It can't predict that if there are no self-employed in the mining sector, then it should just not assign any of them to that sector? I mean how empty is too empty? Hmm I have to think of other possibilities... Best, Lena Den Jun 21, 2012 kl. 2:22 PM skrev Maarten Buis: > I have just seen that you used only the first digit of the ISIC > classification. However, it contains lots of sparse categories(*). > These will cause problems. Also inspect education for sparse > categories. You'll need to combine those sparse categories with > "adjacent" categories in order to get sufficiently filled cells. Also > look at a cross tabulation of industry and education, and see if there > aren't any cells that are too empty. That will probably mean a second > round of merging categories. > > I would not use ordered models or mvn for imputing industry, that just > does not make sense. > > Hope this helps, > Maarten > > (*) If this is recent data from a western country than you have made a > coding error. In that case there are way way way too many farmers. > > On Thu, Jun 21, 2012 at 1:46 PM, Lena Lindbjerg Sperling > <[email protected]> wrote: >>> >>> 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 >>>> -------------------------- >>>> >>>> * >>>> * 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/ > > > > -- > -------------------------- > Maarten L. Buis > Institut fuer Soziologie > Universitaet Tuebingen > Wilhelmstrasse 36 > 72074 Tuebingen > Germany > > > http://www.maartenbuis.nl > -------------------------- > > * > * 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/

**References**:**Fwd: st: Convergence never achieved with MI impute chained***From:*Lena Lindbjerg Sperling <[email protected]>

**Re: st: Convergence never achieved with MI impute chained***From:*Maarten Buis <[email protected]>

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