Given a table of counts specified in ‘dat’ I would like to create a dataframe with 3 columns (race, grp and outcome) and 206 rows. The variable outcome would be 1 if for ascertained, and 0 if ‘missed’.
dat <- structure(list(race = structure(c(1L, 2L, 1L, 2L), levels = c("black",
"nonblack"), class = "factor"), grp = structure(c(1L, 1L, 2L,
2L), levels = c("hbpm", "uc"), class = "factor"), ascertained = c(63,
32, 24, 21), missed = c(5, 3, 49, 9), total = c(68, 35, 73, 30
)), class = "data.frame", row.names = c(NA, -4L))
>Solution :
For each row set race in the output to that race, grp in the output to that group and then generate the appropriate number of 1s and 0s for outcome. The result is 206 x 3.
library(dplyr)
dat %>%
rowwise %>%
summarize(race = race, grp = grp, outcome = rep(1:0, c(ascertained, missed)))
In the example data there are no duplicate race/grp and if that is true in general then it can alternately be written as::
dat %>%
group_by(race, grp) %>%
summarize(outcome = rep(1:0, c(ascertained, missed)), .groups = "drop")