r - chi square test for each row in data frame

Question

I have a data frame containing independent counts of two observers of the same process.

obs.1 <- c(2,10,53,13,12,15,5)
obs.2 <- c(3,12,45,2,7,17,5)
df <- data.frame(obs.1,obs.2)

I want to use a chi-square test (chisq.test in R "MASS") on each row to see if there is a significant difference between obs.1 to obs.2. I would like to add the results (x-squared, p-value) to the df. I have the feeling the apply function is the correct way to implement this but haven't been successful.

Answer 1

Here is another option using dplyr:

library(dplyr)

df %>%
  rowwise() %>% 
  mutate(
    test_stat = chisq.test(c(obs.1, obs.2))$statistic,
    p_val = chisq.test(c(obs.1, obs.2))$p.value
    )