I am working on making a package: https://meghapsimatrix.github.io/simhelpers/index.html
My advisor suggested this:
"It seems like it would be useful to allow the calc_*() functions to operate either on variable names, within a data.frame as specified in res_dat, or _directly on vectors. Paired with dplyr 1.0, the latter would then circumvent the need for
do() and allow for the following syntax:"
results %>% group_by(method) %>% mutate(calc_rejection(p_values = p_val))
"I think there is probably a way to write it so that the
is optional. See the chapter on non-standard evaluation in Hadley's
Advanced R book for pointers. If it's optional, then there's no need to
wait for dplyr 1.0."
Right now the function works like this:
# install.packages("devtools") # devtools::install_github("meghapsimatrix/simhelpers") library(simhelpers) library(tidyverse) welch_res %>% group_by(n1, n2, mean_diff, method) %>% group_modify(~ calc_rejection(.x, p_values = p_val)) %>% kable(digits = 5)
How do I make the function work on grouped data without needing to use do() or group_modify(). Is it possible??
Here is the source code for the function: https://github.com/meghapsimatrix/simhelpers/blob/master/R/calc_rejection.R