问题
I want to calculate a composite score and cronbach's alpha for multiple variables in my data frame and add the results as columns to the data frame.
Here is what my data frame looks like:
t1pp_1 t1pp_2 t1pp_3 t1pp_4 t1se_1 t1se_2 t1se_3 t1se_4 t1cpl_1 t1cpl_2 t1cpl_3 t1cpl_4
6 3 5 3 4 3 4 3 1 2 2 3
7 4 7 6 5 5 4 5 5 5 5 5
4 4 6 5 4 4 4 4 1 2 3 2
5 5 7 5 4 5 4 5 5 4 4 4
4 2 6 6 4 4 3 4 4 4 2 3
6 5 7 5 1 1 4 4 1 2 2 2
Here is what I tried and of course this doesn't work, but maybe it gives you an idea of what I'm aiming at:
library(multicon)
library(psych)
library(dplyr)
comp_and_alph <- function(data = my_data, variable_name) {
dplyr::select(data,contains("variable_name")) %>%
mutate(t1pp_comp = multicon::composite(.)) # is there a way to get the variable name with the '_comp'and '_alph' ending? - Maybe with paste??
mutate(t1_alph = psych::alph(.)) %>%
round(.$total, 2))
}
In the end, I would be very happy if my data frame looked like this (alpha and composite should be rounded and two decimal points displayed):
t1pp_1 t1pp_2 t1pp_3 t1pp_4 t1se_1 t1se_2 t1se_3 t1se_4 t1cpl_1 t1cpl_2 t1cpl_3 t1cpl_4 t1pp_comp t1pp_alph t1se_comp t1se_alph t1cpl_comp t1cpl_alph
6 3 5 3 4 3 4 3 1 2 2 3 3 3 3 3 3 3
7 4 7 6 5 5 4 5 5 5 5 5 5 5 5 5 5 5
4 4 6 5 4 4 4 4 1 2 3 2 2 2 2 2 2 2
5 5 7 5 4 5 4 5 5 4 4 4 4 4 4 4 4 4
4 2 6 6 4 4 3 4 4 4 2 3 3 3 3 3 3 3
6 5 7 5 1 1 4 4 1 2 2 2 2 2 2 2 2 2
I hope this is clear. Please tell me if I'm missing sth. Thanks!
回答1:
The question's problem is divided in the following two functions.
- Function
comp_and_alph
is the question's function corrected, createscomp
andalpha
scores of the columns matching one pattern only. - Function
comp_and_alph_all
matches all patterns invariable_name
.
The functions are meant to work together, preferably calling comp_and_alpha_all
.
comp_and_alph <- function(data = my_data, variable_name, ...) {
data %>%
select(matches(variable_name)) %>%
mutate(comp = composite(.),
alpha = alpha(., ...)$scores) %>%
rename_at(vars(c("comp", "alpha")), ~paste(variable_name, .,sep = "_"))
}
comp_and_alph_all <- function(data, variables, ...){
res <- lapply(variables, function(v){
comp_and_alph(data, v, ...)
})
Reduce(function(x, y){merge(x, y)}, init = list(data), res)
}
comp_and_alph_all(df1, c("t1pp", "t1se"), check.keys = TRUE)
Data.
df1 <-
structure(list(t1pp_1 = c(6L, 7L, 4L, 5L, 4L, 6L), t1pp_2 = c(3L,
4L, 4L, 5L, 2L, 5L), t1pp_3 = c(5L, 7L, 6L, 7L, 6L, 7L), t1pp_4 = c(3L,
6L, 5L, 5L, 6L, 5L), t1se_1 = c(4L, 5L, 4L, 4L, 4L, 1L), t1se_2 = c(3L,
5L, 4L, 5L, 4L, 1L), t1se_3 = c(4L, 4L, 4L, 4L, 3L, 4L), t1se_4 = c(3L,
5L, 4L, 5L, 4L, 4L), t1cpl_1 = c(1L, 5L, 1L, 5L, 4L, 1L), t1cpl_2 = c(2L,
5L, 2L, 4L, 4L, 2L), t1cpl_3 = c(2L, 5L, 3L, 4L, 2L, 2L), t1cpl_4 = c(3L,
5L, 2L, 4L, 3L, 2L)), class = "data.frame", row.names = c(NA, -6L))
来源:https://stackoverflow.com/questions/60054931/r-compute-composite-score-and-cronbachs-alpha-for-multiple-variables-in-a-data