st: Adjusting Post-Stratification weights for Sample Truncation

[Afif Naeem <afeef745@hotmail.com>]

Hello everyone,

I sent out this message couple of days ago, but not sure it actually went through. I am sending it again hoping someone is able to help me out here.

I am working with a data set comprising about 2000 observations on Florida residents. The data set contains information on probability weights to be used with the full sample. The probability weights are calculated through raking procedure so the marginal distributions of the full final sample are optimally fitted to those of the population. Demographic information on eight variables is used as the benchmark for the raking procedure. Base weights controlling for survey design are used as the starting weights in the raking procedure.

I am pretty sure no clustering was used for sampling the individuals for the survey. And I am not worried about stratification of the sample either. Base weight primarily corrects for several sources of deviation from an equal probability of selection design due to change in recruitment method for the panel maintained by the firm conducting the survey over the years.

For my regression analysis, I loose about 600 observations; 400 of them due to missing values of various variables used in the analysis, while I loose the remaining 200 observations because I impose a selection criteria of which individuals are to be included in the regression analysis.

The original post-stratification weights are to be used with the full sample of 2000 observations. My main concern is how to adjust these post-stratification weights so they can be used with my final sample of 1400 observations? Distribution of half of the demographic variables used in the raking procedure change between the full sample of 2000 observations, and my final sample of 1400 observations. I do not have information on some of the demographic variables used in the raking procedure in my data set either. And contacting the firm responsible for conducting the survey is not very feasible as I received the data set through another academic institution which hold the rights to the data. I am wondering if someone can suggest any solution as to how the weights can be adjusted so that they can be used with my final truncated sample of 1400 observations.


Thanks a lot!
Afif 		 	   		  
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