Differences between using a variable as a WEIGHT variable in SPSS and using it as a WLS or regression weight (REGWGT) in REGRESSION
I'm trying to clarify the effects of using the same variable with the WEIGHT command and using it as a regression or WLS weight via the REGWGT subcommand in the SPSS REGRESSION procedure. How will the two approaches affect my regression coefficients, standard errors and other basic regression results?
Resolving the problem
In SPSS, the WEIGHT command is used as a case replication weight. If you have a weight of 2 for a case, that tells SPSS to treat that physical entry in the data file as representing two identical cases. When you use WEIGHT, unless you normalize your weights to have a mean of 1, the N you get reported from a statistical procedure will not match the number of physical cases, as it will be the sum of the weights.
The REGWGT or WLS weight in the REGRESSION procedure is a weight that is generally used to correct for unequal variability or precision in observations, with weights inversely proportional to the relative variability of the data points. The effects on the basic regression analysis of using a regression or WLS weight in REGRESSION are identical to those of using the same variable as a WEIGHT variable, except that the N is not altered