I have a large set of weighted data. I have loaded it into a survey design and would now like to run t-tests on sub-populations.
example:
DF<-cbind(ID, WEIGHT, GENDER, INCOME)
ID WEIGHT GENDER RELOCATE INCOME
[1,] 1 4380 1 1 35
[2,] 2 5000 1 1 20
[3,] 3 0 0 1 55
[4,] 4 5640 1 0 60
[5,] 5 6120 0 1 25
example.survey<-svydesign(ids=~0, data=DF, weights=WEIGHT)
I am able to call the mean income for the entire sample by:
svymean(INCOME, example.survey)
mean SE
[1,] 35.227 9.043
However, I want to compare the means for a subpopulation of this sample so that I can maintain the proper weights.
Can you confirm that this is the proper syntax to run a t-test comparing the mean INCOME based on GENDER for those who relocated (RELOCATE==1)?
svyttest(INCOME~GENDER+RELOCATE==1, example.survey)
data: INCOME ~ GENDER + RELOCATE == 1
t = 0.9841, df = 2, p-value = 0.4288
alternative hypothesis: true difference in mean is not equal to 0
sample estimates:
difference in mean
14.78145
Best Answer
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