I used proc logistic to output a dataset containing initial parameter estimates using OUTEST that I then applied to the proc surveylogistic version of the model using INEST. These parameter estimates served as a starting point for the model convergence. If you have already exhausted all of the ridging options, I would try: Proc logistic data=boot.merged_1 OUTEST=XXXX; class ADHR (ref=first) DHH_SEX (ref=first) year(ref=first) agegrp (ref=first) edu_lv (ref=first) ; model adhr = DHH_SEX year agegrp edu_lv / PARAM=REF ; run; Proc surveylogistic data=boot.merged_1 varmethod=BRR INEST=XXXX ; class ADHR (ref=first) DHH_SEX (ref=first) year(ref=first) agegrp (ref=first) edu_lv (ref=first) ; model adhr = DHH_SEX year agegrp edu_lv / PARAM=REF ; repweights bsw1 - bsw500 ; weight fwgt ; run; The variables from the OUTEST dataset must match the number of variables and the variable names that PROC SURVEYLOGISTIC is expecting from your inputted INEST dataset. If you have a similar model that did converge in PROC SURVEYLOGISTIC, you can use that to investigate what variables are needed. I hope this works. I am far from an expert on this and it may have been luck that this was a quick fix for me.
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