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I have a repeated measures design with categorical variables. Let's say, participants reported their attitude ('Approve', 'Neutral', 'Disapprove') at time point 1 and 2. I then create a table with frequencies of response combinations.

# setup
set.seed(123)
library(tidyverse)

# made-up data
survey.data <- data.frame(
 `1st survey` = c('Approve', 'Approve', 'Neutral', 'Approve'),
 `2nd survey` = c('Approve', 'Disapprove', 'Approve', 'Neutral'),
 `Counts` = c(79, 15, 86, 10),
 check.names = FALSE
) %>%
tidyr::uncount(., Counts) %>%
 tibble::as_tibble()

# table of counts
table("1" = survey.data$`1st survey`, "2" = survey.data$`2nd survey`)
#> 2
#> 1 Approve Disapprove Neutral
#> Approve 79 15 10
#> Neutral 86 0 0

Note here that since nobody chose the option "Disapprove" at time point-1, it is missing from the table. This is, of course, expected. But the function I want to use (rcompanion::cohenG) expects an equal number of rows and columns in a table. So I was wondering how I can change the code above to get the expected output here-

#> 2
#> 1 Approve Disapprove Neutral
#> Approve 79 15 10
#> Disapprove 0 0 0 
#> Neutral 86 0 0

You can cast the responses to factors with three known levels

levels <- c("Disapprove", "Neutral", "Approve")

survey.data <- survey.data %>%
 mutate_at(vars(`1st survey`,
 `2nd survey`),
 factor, levels = levels)

table(survey.data$`1st survey`,
 survey.data$`2nd survey`)
#> 
#> Disapprove Neutral Approve
#> Disapprove 0 0 0
#> Neutral 0 0 86
#> Approve 15 10 79

^{Created on 2019-03-08 by the reprex package (v0.2.1)}