A helper function to help you format the participants data (age, sex, ...) in the participants section.
Usage
report_participants(
data,
age = NULL,
sex = NULL,
gender = NULL,
education = NULL,
participants = NULL,
group = NULL,
spell_n = FALSE,
digits = 1,
...
)
Arguments
- data
A data frame.
- age
The name of the column containing the age of the participant.
- sex
The name of the column containing the sex of the participant. The classes should be one of
c("Male", "M", "Female", "F")
. Note that you can specify other characters here as well (e.g.,"Intersex"
), but the function will group all individuals in those groups as"Other"
.- gender
The name of the column containing the gender of the The classes should be one of
c("Man", "M", "Woman", "F", "Non-Binary", "N")
. Note that you can specify other characters here as well (e.g.,"Gender Fluid"
), but the function will group all individuals in those groups as"Non-Binary"
.- education
The name of the column containing education information.
- participants
The name of the participants' identifier column (for instance in the case of repeated measures).
- group
A character vector indicating the name(s) of the column(s) used for stratified description.
- spell_n
Fully spell the sample size (
"Three participants"
instead of"3 participants"
).- digits
Number of significant digits.
- ...
Arguments passed to or from other methods.
Value
A character vector with description of the "participants", based on
the information provided in data
.
Examples
library(report)
data <- data.frame(
"Age" = c(22, 23, 54, 21, 8, 42),
"Sex" = c("Intersex", "F", "M", "M", "M", "F"),
"Gender" = c("N", "W", "W", "M", "M", "M")
)
report_participants(data, age = "Age", sex = "Sex")
#> [1] "6 participants (Mean age = 28.3, SD = 16.6, range: [8, 54]; Sex: 33.3% females, 50.0% males, 16.7% other; Gender: 33.3% women, 50.0% men, 16.67% non-binary)"
# Years of education (relative to high school graduation)
data$Education <- c(0, 8, -3, -5, 3, 5)
report_participants(data,
age = "Age", sex = "Sex", gender = "Gender",
education = "Education"
)
#> [1] "6 participants (Mean age = 28.3, SD = 16.6, range: [8, 54]; Sex: 33.3% females, 50.0% males, 16.7% other; Gender: 33.3% women, 50.0% men, 16.67% non-binary; Mean education = 1.3, SD = 4.9, range: [-5, 8])"
# Education as factor
data$Education2 <- c(
"Bachelor", "PhD", "Highschool",
"Highschool", "Bachelor", "Bachelor"
)
report_participants(data, age = "Age", sex = "Sex", gender = "Gender", education = "Education2")
#> [1] "6 participants (Mean age = 28.3, SD = 16.6, range: [8, 54]; Sex: 33.3% females, 50.0% males, 16.7% other; Gender: 33.3% women, 50.0% men, 16.67% non-binary; Education: Bachelor, 50.00%; Highschool, 33.33%; PhD, 16.67%)"
# Repeated measures data
data <- data.frame(
"Age" = c(22, 22, 54, 54, 8, 8),
"Sex" = c("I", "F", "M", "M", "F", "F"),
"Gender" = c("N", "W", "W", "M", "M", "M"),
"Participant" = c("S1", "S1", "s2", "s2", "s3", "s3")
)
report_participants(data, age = "Age", sex = "Sex", gender = "Gender", participants = "Participant")
#> [1] "3 participants (Mean age = 28.0, SD = 23.6, range: [8, 54]; Sex: 33.3% females, 33.3% males, 33.3% other; Gender: 33.3% women, 33.3% men, 33.33% non-binary)"
# Grouped data
data <- data.frame(
"Age" = c(22, 22, 54, 54, 8, 8, 42, 42),
"Sex" = c("I", "I", "M", "M", "F", "F", "F", "F"),
"Gender" = c("N", "N", "W", "M", "M", "M", "Non-Binary", "Non-Binary"),
"Participant" = c("S1", "S1", "s2", "s2", "s3", "s3", "s4", "s4"),
"Condition" = c("A", "A", "A", "A", "B", "B", "B", "B")
)
report_participants(data,
age = "Age",
sex = "Sex",
gender = "Gender",
participants = "Participant",
group = "Condition"
)
#> [1] "For the 'Condition - A' group: 2 participants (Mean age = 38.0, SD = 22.6, range: [22, 54]; Sex: 0.0% females, 50.0% males, 50.0% other; Gender: 50.0% women, 0.0% men, 50.00% non-binary) and for the 'Condition - B' group: 2 participants (Mean age = 25.0, SD = 24.0, range: [8, 42]; Sex: 100.0% females, 0.0% males, 0.0% other; Gender: 0.0% women, 50.0% men, 50.00% non-binary)"
# Spell sample size
paste(
report_participants(data, participants = "Participant", spell_n = TRUE),
"were recruited in the study by means of torture and coercion."
)
#> [1] "Four participants (Mean age = 31.5, SD = 20.5, range: [8, 54]; Sex: 50.0% females, 25.0% males, 25.0% other; Gender: 25.0% women, 25.0% men, 50.00% non-binary) were recruited in the study by means of torture and coercion."