survey weighted t test not showing correct difference in mean in r?

I am doing an analysis with complex survey data in R. However when I use svyttest from the survey package to preform a design base t-test, it is not providing the correct difference in mean

svyby(~preds,~SDDSRVYR,svymean, design=subset(data, age==2))
   SDDSRVYR     preds         se
7         7 0.2340050 0.01161363
10       10 0.3159294 0.01076532

tt<-svyttest(preds~SDDSRVYR, design=subset(data, age==2))
> tt

    Design-based t-test

data:  preds ~ SDDSRVYR
t = 5.1734, df = 30, p-value = 1.428e-05
alternative hypothesis: true difference in mean is not equal to 0
95 percent confidence interval:
 0.01696236 0.03765392
sample estimates:
difference in mean 
        0.02730814

As you can see, the difference in means is about 0.082, but the t test is showing its 0.03. Am I not understanding how the t-test is calculating the means? I can't imagine it would be any different than svymean...Or perhaps this is a coding issue?

Solution

I found the answer-SDDSRVYR was being treated as continuous (it takes the values 7 and 10). Not binary

svyttest(preds~factor(SDDSRVYR), design=subset(data, age==2))

Design-based t-test

data:  preds ~ factor(SDDSRVYR)
t = 5.1734, df = 30, p-value = 1.428e-05
alternative hypothesis: true difference in mean is not equal to 0
95 percent confidence interval:
 0.05088707 0.11296176
sample estimates:
difference in mean 
        0.08192442