Hi all,

I'm trying to perform chained multiple imputations but get an error message about convergence. My variables are not highly correlated with one another. I end up with 15,600 - 23,700 observations at the end though (I initially had a maximum of 698 observations). Any thoughts about what I should do?
Below are my code, the error message I get and some screenshots with information about my data
Thanks

Data
24 potential covariate factors that I will have to correlate with my DVs and IV to choose which ones to include in my final regression model
3 continuous DVs that I will independently examine (VS, PL, CE)
1 categorical variable with 6 categories (traj_alcohol) - does not have missing data (Note. I tried to include a "=" sign and place this variable on the right-hand side but I had an error message about having missing data in it)

Code
Code:
mi set mlong

mi register imputed post_smoking preeclampsia preterm pregnancy_planning DASS_stress DASS_anx DASS_depr parity parenting diet mat_ment_health folate fad ethnicity psy breastfeed antidep_combined SRI SGA BMI ax drug VS PL CE child_sex  pren_smoking traj_alcohol

mi impute chained (regress) mat_ment_health parity folate fad VS PL CE (logit, augment) ethnicity pregnancy_planning SRI preeclampsia preterm SGA drug DASS_stress DASS_depr DASS_anx antidep_combined post_smoking (mlogit, augment) psy breastfeed parenting BMI diet ax = traj_alcohol child_sex pren_smoking, add(43) noisily

Output
Code:
Note: 92 failures and 1 success completely determined.
convergence not achieved
logit failed to converge on observed data
error occurred during imputation of mat_ment_health parity folate fad VS PL CE ethnicity pregnancy_planning SRI preeclampsia preterm SGA drug
DASS_stress DASS_depr DASS_anx antidep_combined post_smoking psy breastfeed parenting BMI diet ax on m = 4
Screenshots
Summary of my variables post imputation
Variable manager view