I need to calculate the frequency of individuals by age and marital status so normally I'd use:
table(age, marital_status)
However each individual has a different weight after the sampling of the data. How do I incorporate this into my frequency table?
You can use function svytable
from package survey
, or wtd.table
from rgrs
.
EDIT : rgrs
is now called questionr
:
df <- data.frame(var = c("A", "A", "B", "B"), wt = c(30, 10, 20, 40))
library(questionr)
wtd.table(x = df$var, weights = df$wt)
# A B
# 40 60
That's also possible with dplyr
:
library(dplyr)
count(x = df, var, wt = wt)
# # A tibble: 2 x 2
# var n
# <fctr> <dbl>
# 1 A 40
# 2 B 60
Using data.table
you could do:
# using the same data as Victorp
setDT(df)[, .(n = sum(wt)), var]
var n
1: A 40
2: B 60
You can also use tablefreq from package freqweights:
df <- data.frame(var = c("A", "A", "B", "B"), wt = c(30, 10, 20, 40))
library(freqweights)
tablefreq(df, "var", "wt")
A tibble: 2 x 2
var freq
<fct> <dbl>
1 A 40
2 B 60
来源:https://stackoverflow.com/questions/18585977/frequency-tables-with-weighted-data-in-r