I am having difficulty understanding random stratified sampling when there are nested categories within them. Take for instance a size of 1000, and you are interested in sampling gender and smoking. Lets assum there are 500 females, so does that mean you create a first gender stratum with 500 females and 500 males. Subseqeuntly you randomly select participants from each gender category, and then create a second strata within each gender categories for smoker vs. and non-smoker. Then you select a random sample from each of these cateogory. Is that how stratified random sampling works? Because that sounds like multi-stage sampling to me? Please help I'm trying to visualise how it all works.
In your example gender likely doesn't need to sample d only collected. Could you please send another example. Best wishes David Booth BTW WHY DO YOU assume 500 females you could be sampling from a men's prison..
David Eugene Booth thank you, i merely assumed because I am trying to figure out the steps involved in doing random stratified sampling, when there are 2 categories nested within each other. I have a sample of about a million participants from national statistics, and i need to figure out how to stratify them so that they become nationally representatve of gender, age, ethnicity and education.
BTW you might want to look at attached screenshot for a starting book. Further remember the subsamples that you choose could be different kinds of samples which can be a real complication. Starting small and working up is my suggestion. BTW the book can be found in the z-library.. David Booth
From your second post I suggest you consult a sampling expert or simplify things so each sample is a simple random sample. I still would not be comfortable that I could solve that problem in a finite amount of time
Best wishes David Booth
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