Hello,
I'm using a complex survey dataset and my goal is to simply spit out a bunch of
probability-weighted outcome variable means for the different levels of
covariate. So I first define the structure of the study design (I'm using the
CDC's NHANES data):
dhanes <- svydesign(id=~PSU, strat=~STRATA, weight=~lab_weight, data=final,
nest=TRUE)
No problem there.
Now I use the "svyby" function as follows:
svyby(~outcome, ~covariate, design=dhanes, svymean, na.rm=T) -> haha
print(haha)
covariate outcome se.outcome
1 1 0.4961189 0.08828457
2 2 0.4474706 0.22214557
3 3 0.5157026 0.12076008
4 4 0.6773910 0.20605025
NA NA 0.8728167 0.15622274
...and it works just fine. I get a nice table of the mean and standard error
for each level of the covariate. I started writing a custom function to
automate this and I had problems. Consider this really basic custom function
(that does not seem very different from the above code):
this_is_a_test <-function(outcome, covariate)
{
svyby(~outcome, ~covariate, design=dhanes, svymean, na.rm=T) -> haha
print(hah)
}
I get the following output:
Error in `[.survey.design2`(design, nas == 0, ) :
(subscript) logical subscript too long
I really don't understand this because I haven't done anything too different.
Before I can even start writing up the rest of the function, I have to settle
this. Any ideas?
-Roni
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