sampling weights

#1
Hi,

I am using a national dataset for my analysis. I am confused with the sampling weight because my understanding of sampling weights is to compensate disproportionate stratification, such as gender, SES, educational level, area, etc. However, if I use a variable, such as frequent vs infrequent exercise, without incorporating gender, SES, area variables, do I still need to take sampling weights into account?

Any comments are highly valued.

Thank you.
 

Lazar

Phineas Packard
#2
Yes. You should use the sampling weights for all analyses as the weights aim to give estimates which are more consistent with a truely representative sample.
 
#3
Hi Lazar,
Thanks for the prompt reply. Please forgive me for not having sufficient stat knowledge. What should I do to take care of sampling weights? Should I recalculate another set of value or does estimation method (Mplus) take care of that problem?
If I divided number of times exercise per week into two groups to analyze a set of attitudinal variables rated on 5-point scale (treated as continuous), should I use the sampling weights for the two groups or the attitudinal variables?

Thanks.

Any comments are appreciated.