Hi,
I am using a standard DHS-VI survey dataset for Pakistan 2012-13. It is a survey cross-section data with sample weights. My response variable is a binary variable indicating whether a child has ARI or not. On the right hand side I have some covariates. I want to control for heterogeneity across districts but employing the fixed effects model by using districts as my group variable. Now, there are two ways that I am familiar with that I can use to this.
1- svy:logistic y x1 x2 x3 i.dist
2- xtlogit y x1 x2 x3, fe or (when I use weights here it gives error 'weights should be same across all groups)
I want to know which approach would be the right way to do this as I know fixed effects are usually done on panel data. I was told that if I use the 1st approach then I might face 'incremental parameter problem'. Please help.
I am using a standard DHS-VI survey dataset for Pakistan 2012-13. It is a survey cross-section data with sample weights. My response variable is a binary variable indicating whether a child has ARI or not. On the right hand side I have some covariates. I want to control for heterogeneity across districts but employing the fixed effects model by using districts as my group variable. Now, there are two ways that I am familiar with that I can use to this.
1- svy:logistic y x1 x2 x3 i.dist
2- xtlogit y x1 x2 x3, fe or (when I use weights here it gives error 'weights should be same across all groups)
I want to know which approach would be the right way to do this as I know fixed effects are usually done on panel data. I was told that if I use the 1st approach then I might face 'incremental parameter problem'. Please help.
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