I had the theory in grad school, but have not implemented. So I am instructing my SAS programmer colleague on what I want.
I am looking at a U.S. natl survey. The sample is multi-tiered. One of the variables is finalwgt, defined as Final Weight after accounting for strata, clusters, etc.
1. For finding the mean for a variable like age, what PROC do I tell him to use to incorporate the weights into the Point Estimate and the Standard Error?
2. Am I still on safe ground, if we have censored all the non-respondents?
Now for the tricky part. We are manipulating a couple of variables to produce a Yes-No measure, and we are censoring non-response. Then we want to find percent Yes.
In my mind, we multiply the weights times the zeros and ones. We sum the new column and divide by the sum of the weights (including the Yes and No, but omitting the non-response).
3. Does this make sense to you for a point estimate?
4. How do I instruct him to derive a confidence interval for the percent Yes?
TIA
I am looking at a U.S. natl survey. The sample is multi-tiered. One of the variables is finalwgt, defined as Final Weight after accounting for strata, clusters, etc.
1. For finding the mean for a variable like age, what PROC do I tell him to use to incorporate the weights into the Point Estimate and the Standard Error?
2. Am I still on safe ground, if we have censored all the non-respondents?
Now for the tricky part. We are manipulating a couple of variables to produce a Yes-No measure, and we are censoring non-response. Then we want to find percent Yes.
In my mind, we multiply the weights times the zeros and ones. We sum the new column and divide by the sum of the weights (including the Yes and No, but omitting the non-response).
3. Does this make sense to you for a point estimate?
4. How do I instruct him to derive a confidence interval for the percent Yes?
TIA