I conducted a mediation analysis using gsem with survey data because my mediators are count data and I set them as negative binomial variables. Consequently, gsem does not allow for the same model-fit commands as sem and so I am curious how people publish their findings utilizing gsem. Below is my syntax. I obtained estimates of the indirect and total effects and now just need model-fit information. I have read several threads on gsem post estimation commands without much luck and would greatly appreciate feedback.
svy linearized, subpop(domain_interest): gsem (Child_Gender -> Wave3_Ext, ) (chdAgeY -> Wave3_Ext, ) (CG_Gender -> Wave3_Ext, ) (Wave1_Ext -> Wave3_Ext, ) ///
(PPH_MCS -> DS3_NGPR, family(nbinomial constant) link(log)) (PPH_MCS -> DS3_AGPR, family(nbinomial constant) link(log)) /// (PPH_MCS -> Wave3_Ext ) ///
(DS3_NGPR -> Wave3_Ext, ) (DS3_AGPR -> Wave3_Ext, ) [=], nocapslatent
gsem, coeflegend
nlcom _b[Wave3_Ext:DS3_NGPR]*_b[DS3_NGPR:PPH_MCS]
nlcom _b[Wave3_Ext:PPH_MCS]+_b[Wave3_Ext:DS3_NGPR]*_b[DS3_NGPR:PPH_MCS]
nlcom _b[Wave3_Ext:DS3_AGPR]* _b[DS3_AGPR:PPH_MCS]
nlcom _b[Wave3_Ext:PPH_MCS]+_b[Wave3_Ext:DS3_AGPR]* _b[DS3_AGPR:PPH_MCS]
svy linearized, subpop(domain_interest): gsem (Child_Gender -> Wave3_Ext, ) (chdAgeY -> Wave3_Ext, ) (CG_Gender -> Wave3_Ext, ) (Wave1_Ext -> Wave3_Ext, ) ///
(PPH_MCS -> DS3_NGPR, family(nbinomial constant) link(log)) (PPH_MCS -> DS3_AGPR, family(nbinomial constant) link(log)) /// (PPH_MCS -> Wave3_Ext ) ///
(DS3_NGPR -> Wave3_Ext, ) (DS3_AGPR -> Wave3_Ext, ) [=], nocapslatent
gsem, coeflegend
nlcom _b[Wave3_Ext:DS3_NGPR]*_b[DS3_NGPR:PPH_MCS]
nlcom _b[Wave3_Ext:PPH_MCS]+_b[Wave3_Ext:DS3_NGPR]*_b[DS3_NGPR:PPH_MCS]
nlcom _b[Wave3_Ext:DS3_AGPR]* _b[DS3_AGPR:PPH_MCS]
nlcom _b[Wave3_Ext:PPH_MCS]+_b[Wave3_Ext:DS3_AGPR]* _b[DS3_AGPR:PPH_MCS]
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