Dear Statalist:
I'm trying to test a hypothesis by looking at how much more variance is
explained (measured by increased R-squared) when I add test variables to my
model. Because I'm using a dataset with complex sampling weights, I need to
use the survey (svy) commands.
So I am using the svylogit command for all my multivariate analyses on
dichotomous outcome variables. But svylogit does not produce an R2 value. Is
there another command that will produce this R2 value for me? Or does Stata
have another measure--other than R2--that measures how much variance a model
explains when using complex survey data? (I believe the logit command *does*
return an R2 result, so I'm not sure why svylogit doesn't. Is there
something about complex survey data that makes R2 values inappropriate?)
My understanding is that the svytest command will not do this for me (i.e.
it can used as a partial F-test to test the significance of individual
variables or groups of dummy variables, but not for whole models).
I've received all of my stats training in SPSS (I know, I know... boo hiss!)
so forgive me for my ignorance! I've looked over the manuals and the
Statalist archives but can't find what I'm looking for.
Thanks!
Karen
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