this is my first time posting a question here so be easy on me, let me know if you have tips for making my questions clearer.
I'm trying to initiate a function that will summarize given columns by group ("c", "e"), which I've initialized as shown below, but the output seems to ignore the grouping factor when I pass the parameters into the function (df, x). How can I ensure that grouping is respected when applying the custom summary function?
#initialize and relevel factor
dexadf$group <- factor(dexadf$group, levels=c("c", "e"),
labels = c("c", "e"))
dexadf$group <- relevel(dexadf$group, ref="c")
attributes(dexadf$group)
My data looks like this, I've only included 1 of the columns of interest (fm_bdc3) for sake of simplicity:
> dput(dexadf)
structure(list(participant = c("pt04", "pt75", "pt21", "pt73",
"pt27", "pt39", "pt43", "pt52", "pt69", "pt49", "pt50", "pt56",
"pt62", "pt68", "pt22", "pt64", "pt54", "pt79", "pt36", "pt26",
"pt65", "pt38"), group = structure(c(1L, 2L, 2L, 1L, 1L, 2L,
1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L
), .Label = c("c", "e"), class = "factor"),
fm_bdc3 = c(18.535199635968, 23.52996574649, 17.276246451976,
11.526088555461, 23.805048656112, 23.08597823716, 28.691020942436,
28.968097858499, 23.378093165331, 22.491725344661, 14.609015054932,
19.734914019306, 31.947412973684, 25.152298171274, 12.007356801787,
20.836128108938, 22.322230884349, 14.777652101515, 21.389572717608,
16.992853675086, 14.138189878472, 17.777235203826)
→ function:
summbygrp <- function(df, x) {
group_by(df, group) %>%
summarise(
count = n(),
mean = mean(x, na.rm = TRUE),
sd = sd(x, na.rm = TRUE)
) %>%
mutate(se = sd / sqrt(11),
lower.ci = mean - qt(1 - (0.05 / 2), 11 - 1) * se,
upper.ci = mean qt(1 - (0.05 / 2), 11 - 1) * se
)
}
→ function output:
> summbygrp(dexadf, fm_bdc3)
# A tibble: 2 × 7
group count mean sd se lower.ci upper.ci
<fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
1 c 11 20.6 5.48 1.65 16.9 24.3
2 e 11 20.6 5.48 1.65 16.9 24.3
As you can see, the summaries of both groups are identical, and I know this not to be true. Can someone identify the error in my code?
Here is the output if I don't use a function, but I have many columns so this would be pretty tedious to create for each column
group_by(dexadf, group) %>%
summarise(
count = n(),
mean = mean(fm_bdc3, na.rm = TRUE),
sd = sd(fm_bdc3, na.rm = TRUE)
) %>%
mutate(se = sd / sqrt(11),
lower.ci = mean - qt(1 - (0.05 / 2), 11 - 1) * se,
upper.ci = mean qt(1 - (0.05 / 2), 11 - 1) * se
)
→ correct ouput:
# A tibble: 2 × 7
group count mean sd se lower.ci upper.ci
<fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
1 c 11 19.3 5.49 1.66 15.6 23.0
2 e 11 21.9 5.40 1.63 18.2 25.5
CodePudding user response：
library(dplyr)
library(rlang)
dexadf <- data.frame(
stringsAsFactors = FALSE,
participant = c("pt04","pt75","pt21","pt73",
"pt27","pt39","pt43","pt52","pt69","pt49","pt50",
"pt56","pt62","pt68","pt22","pt64","pt54","pt79",
"pt36","pt26","pt65","pt38"),
fm_bdc3 = c(18.535199635968,23.52996574649,
17.276246451976,11.526088555461,23.805048656112,
23.08597823716,28.691020942436,28.968097858499,
23.378093165331,22.491725344661,14.609015054932,19.734914019306,
31.947412973684,25.152298171274,12.007356801787,
20.836128108938,22.322230884349,14.777652101515,
21.389572717608,16.992853675086,14.138189878472,17.777235203826),
group = as.factor(c("c","e",
"e","c","c","e","c","e","c","e","e","c",
"e","c","c","e","e","c","e","c","e",
"c")),
sex = as.factor(c("f","m",
"m","m","m","m","m","f","m","f","f","f",
"f","f","f","f","m","f","m","m","f",
"m"))
)
summbygrp <- function(df, x) {
group_by(df, group) %>%
summarise(
count = n(),
mean = mean({{x}}, na.rm = TRUE),
sd = sd({{x}}, na.rm = TRUE)
) %>%
mutate(se = sd / sqrt(11),
lower.ci = mean - qt(1 - (0.05 / 2), 11 - 1) * se,
upper.ci = mean qt(1 - (0.05 / 2), 11 - 1) * se
)
}
summbygrp(dexadf, fm_bdc3)
#> # A tibble: 2 × 7
#> group count mean sd se lower.ci upper.ci
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 c 11 19.3 5.49 1.66 15.6 23.0
#> 2 e 11 21.9 5.40 1.63 18.2 25.5
Created on 2022-07-09 by the reprex package (v2.0.1)
Why this works
You actually need to use {{}}, pronounced as curly-curly, from rlang package to make this function work. When you want to pass varibales (i.e. columns of a dataset) as function parameters inside a function which uses dplyr or other tidyverse verbs (like mutate, summarise, group_by etc.), you need to wrap those parameter inside curly-curly like here we did with x. Otherwise the function won't work as intended and most probably throw erros. Because tidyverse verbs uses NSE (Non-Standard Evaluation). To know more, check out this Programming with dplyr and also I would encourage you to read chapters 17-20 of the book Advanced R
CodePudding user response：
an add-on question:
could you also help with this forloop that I'm using to apply the function to all columns in dexadf? Regardless of my function working on it's own, if I use it in the forloop it returns an output for every column with the exact same problem as before.
summbygrp <- function(x) {
group_by(dexadf, group) %>%
summarise(
count = n(),
mean = mean({{x}}, na.rm = TRUE),
sd = sd({{x}}, na.rm = TRUE)
) %>%
mutate(se = sd / sqrt(11),
lower.ci = mean - qt(1 - (0.05 / 2), 11 - 1) * se,
upper.ci = mean qt(1 - (0.05 / 2), 11 - 1) * se
)
}
coln = 1
for (col in dexadf) {
print(colnames(dexadf)[coln])
if(is.numeric(col)) {
print(summbygrp(col))
} else {next}
coln = coln 1
}
example outputs:
[1] "legslsm_percchg"
# A tibble: 2 × 7
group count mean sd se lower.ci upper.ci
<fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
1 c 11 -0.286 0.732 0.221 -0.778 0.206
2 e 11 -0.286 0.732 0.221 -0.778 0.206
[1] "trunklsm_bdc3"
# A tibble: 2 × 7
group count mean sd se lower.ci upper.ci
<fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
1 c 11 -0.0126 0.0355 0.0107 -0.0365 0.0112
2 e 11 -0.0126 0.0355 0.0107 -0.0365 0.0112