Survey package and counting

It is not necessary to use the survey, especially for simpler procedures. In this case, a simple aggregate() would be enough for you. I do not have PNAD data on my computer right now, but here's an example:

library(survey)
dados <- data.frame(Peso = rchisq(100, 10), Idade = rnorm(100, 40, 10))

delineamento <- svydesign(ids = ~ 1, weights = ~ Peso, data = dados)
svytable(~ Idade > 30, delineamento)

aggregate(Peso ~ Idade > 30, dados, FUN = sum)

Note that the 2 results are the same. It is important to note that a simple table() does not serve because each observation has different weight.

with(dados, table(Idade > 30))

I wrote a post on the blog survey , you may find it helpful (especially the links in the comments).

I do not know the survey package, but I like to stick to the basic functions of R to solve any problem before resorting to an extra package.

Since you did not provide data as an example, I'll use the embedded base mtcars

head(mtcars)
                   mpg cyl disp  hp drat    wt  qsec vs am gear carb
Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

To know how many cases there are for each value, just use the table function. Remember that we speak of counting / frequency only with discrete or categorical variables:

> table(mtcars$gear)

 3  4  5 
15 12  5 

That is, there are 15 cases with gear == 3 , 12 with gear == 4 and 5 with gear == 5 . The same can be done by "crossing variables":

> table(mtcars$carb , mtcars$gear)

    3 4 5
  1 3 4 0
  2 4 4 2
  3 3 0 0
  4 5 4 1
  6 0 0 1
  8 0 0 1