I have a model with 6 exposure variables and some other covariates. I would like to analyse whether the associations between each of the 6 exposures and the outcome are different for boys and girls. However, I am not sure what the best way to do this is. Should I include an interaction term between sex and each of the exposures:
Code:
regress outcome (c.X1 c.X2 c.X3 c.X4 c.X5 c.X6)##i.sex Maternal_age i.Maternal_edu i.Parity i.SMOKING_X
Or are there other options in Stata 15 that could be better, for example the -suest-? For example.
Code:
regress outcome X1 X2 X3 X4 X5 X6 Maternal_age i.Maternal_edu i.Parity i.SMOKING_X if sex==1 est store m1 regress outcome X1 X2 X3 X4 X5 X6 Maternal_age i.Maternal_edu i.Parity i.SMOKING_X if sex==2 est store m2 suest m1 m2 test [m1_mean]X1=[m2_mean]X1 test [m1_mean]X2=[m2_mean]X2 test [m1_mean]X3=[m2_mean]X3 test [m1_mean]X4=[m2_mean]X4 test [m1_mean]X5=[m2_mean]X5 test [m1_mean]X6=[m2_mean]X6
Kjell Weyde
0 Response to Stratify or include interaaction terms when assessing the associations for boys and girls between several exposure variables and outcome
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