- update the runmlwin-procedure: does not make any difference.
- surpressing the errors on convergence by using the errorok-option and storing the results with the mi saving. This seemed to work but at a giving moment it errored again saying
I can provide you with my latest code:no imputations to compute between-imputation variance no results will be saved r(2000);
Code: Select all
xi: mi estimate, esampvaryok cmdok post: runmlwin move_a /*
*/ cons /*
*/ age_child age_child2 gndr_child i.edu3_child i.mstat_child i.employ_child distance_child_z siblings /*
*/ i.recent_child transfer_child receive_child /*
*/ help_child_hh i.help_child_int2 /*
*/ i.mstat i.edu3 extrahh hinc parent_move iadlmean urban owner/*
*/ formal_care /*
*/ i.country if selection > 1 & age_child >= -22.00958, /*
*/ forcesort level2(couplelevel2: cons, diagonal) level1(n) discrete(dist(multinomial) link(mlogit) denom(cons) basecategory(0)) maxiterations(150) initsv(V) initsb(c) mcmc(on) nopause
1) Turn off the maxiterations?
2) Is it a problem for MCMC-estimation to use esampvaryok? I use this because one of my selection-variables (see "if") is imputed and therefore varies between the imputed datasets.
Given the size, providing the dataset is difficult unless I could wetransfer it, or...?