Combining surveys with distinct analytical weights

[Rio Ferdinand]

Hi.

I have a dataset which combine 14 household surveys in 14 countries. Each survey was conducted in different years and each survey has a household weight variable that only specifies to this country's context (data structure is the same across 14 countries). Now I merged them and tried to cross tabulate the country and gender_area (four types of value: male_rural, female_rural, male_urban, female_urban) variable with weights (tab country gender [aw=hhweight], m). But I found that such a cross-tabulation would create weird values for some of the countries.

For example, if I add one if condition by the end of the tab (tab country gender [aw=hhweight] if abc==1, m), some country (KHM, NPL) 's row total would be greater than their original row total without the condition. But in this dataset, a condition would give a smaller subsample. If I don't add the weight (tab country gender, m), there is no such a problem. If I just tab one country with weight, there is no such a problem either. So I wonder if there is any way for me to compare all countries with weight. I am not that familiar with survey data reference in Stata (svyset, strata, etc). Hopefully there is someone can help.

[Daniel Schaefer]

You should not use Stata's if statement to analyze a subpopulation when you have a complex survey design. Use the survey prefix with the subpop() option instead. Check the svy documentation for the details. My other suggestion would be to thoroughly familiarize yourself with the documentation and find a good textbook. I would recommend Berglund, Herringa, and West (2020) "Applied Survey Data Analysis." It's the second edition. There are plenty of examples of Stata code throughout.

[ericmelse]

To add to the recommendation of Daniel, here is a website that provides the data and examples of the ASDA-first and second edition as well as many references related to this subject.

[Rio Ferdinand]

Thanks, Daniel and Eric. I will try to see if there is any useful information in the book you mentioned. Meanwhile, since it is an urgent issue related to some dataset which will be published soon, I still hope that someone who is an expert in this field can provide some help.