Dear all,
I am using survey data collecting information on consumer conditions, such as consumer knowledge, trust in consumer organisations etc.
I am currently running some analyses to determine differences in these "consumer conditions" across various socio-demographic groups for which information is available in the survey.
The consumer knowledge indicator for instance equals to the total of correct answers a consumer gave on several answers in the survey.
In a first descriptive analysis I use the following "pwmean commands" to obtain the means for the survey-weigthed consumer knowledge indicator (knowledge_tot=knowledge_tot*w1) per socio-demographic group.
I define the code as follows (I add the option "groups" to obtain codes that group them with other means that are not significantly different)
pwmean knowledge_tot_w, over(age) effects groups
pwmean knowledge_tot_w, over(gender) effects groups
pwmean knowledge_tot_w, over(education) effects groups
In a second analysis I run a Poisson model (weighted for the survey data) with the consumer knowledge indicator as dependent variable and the socio-demographic groups as explanatory variables.
The code I run is as such:
xi: poisson knowledge_tot i.age i.gender i.education i.occupation i.internet_use i.living i.phone i.language i.financial i.numerical_skills i.region [iweight=w1] if sample==1, vce(robust)
I calculate average marginal effects as such:
margins , dydx(*)
I would like to know whether the average marginal effect of the first age group is statistically different from the one of the second age group, etc. In a sense I am searching to get similar Stata tables as produced by pwmean (see above), but then for the average marginal effects.
Is this possible? I found out that pwcompare may help me out but I don't get the syntax working.
Many thanks for your help.
Best regards,
Vincent
I am using survey data collecting information on consumer conditions, such as consumer knowledge, trust in consumer organisations etc.
I am currently running some analyses to determine differences in these "consumer conditions" across various socio-demographic groups for which information is available in the survey.
The consumer knowledge indicator for instance equals to the total of correct answers a consumer gave on several answers in the survey.
In a first descriptive analysis I use the following "pwmean commands" to obtain the means for the survey-weigthed consumer knowledge indicator (knowledge_tot=knowledge_tot*w1) per socio-demographic group.
I define the code as follows (I add the option "groups" to obtain codes that group them with other means that are not significantly different)
pwmean knowledge_tot_w, over(age) effects groups
pwmean knowledge_tot_w, over(gender) effects groups
pwmean knowledge_tot_w, over(education) effects groups
In a second analysis I run a Poisson model (weighted for the survey data) with the consumer knowledge indicator as dependent variable and the socio-demographic groups as explanatory variables.
The code I run is as such:
xi: poisson knowledge_tot i.age i.gender i.education i.occupation i.internet_use i.living i.phone i.language i.financial i.numerical_skills i.region [iweight=w1] if sample==1, vce(robust)
I calculate average marginal effects as such:
margins , dydx(*)
I would like to know whether the average marginal effect of the first age group is statistically different from the one of the second age group, etc. In a sense I am searching to get similar Stata tables as produced by pwmean (see above), but then for the average marginal effects.
Is this possible? I found out that pwcompare may help me out but I don't get the syntax working.
Many thanks for your help.
Best regards,
Vincent
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