I am doing an analysis using National Inpatient Sample which uses a complex survey design and provides weights to project national estimates. My unweighted study sample is about 1000 and weighted is about 5000. Recommendations are to use “svy” commands while working on survey data. My questions are-
- While performing a logistic regression analysis, I was told that I can do it 2 ways:
a.) Using “svy: logit dep(var) indep(var), or” command. If I do this, the number of observations remain 1000 and population is 5000.
b.) Expanding the dataset using “expand weight” command and then running “logit dep(var) indep(var), or” on the expanded sample. Here the number of observations are 5000.
They both make sense and I have tried using both but they have slightly different results in terms of p values.
2.) I can’t calculate “median(IQR)” using “svy” commands. So what’s the alternative for measuring non-parametric continuous variables in such samples. The way I did it- expanded the sample using weights and then ran the command “sum variable, d” on 5000 patients. Is it appropriate? If I don’t expand the weights, my sample size remains 1000.
3.) What is the correct method to determine p values of trends in the categorical variables in the survey sample (for example- % of males who were admitted with myocardial infarction in last 10 years) and continuous variables (length of stay over the years). The recommended official command to determine p-value of trends in categorical variable is- “nptrend”. For continuous variables, linear regression is suggested. Agina, I am not sure how to take into account the survey design while doing this, so I am running these commands after expanding the dataset. Is there a more appropriate way?
I would really appreciate any help.