Title Function designed for use in dplyr (tidyverse) piping to return mean diff and bootstrap CI around that
getBootCIgrpMeanDiff.Rd
Title Function designed for use in dplyr (tidyverse) piping to return mean diff and bootstrap CI around that
Arguments
- formula1
formula defining the two variables to be correlated as scores ~ group
- data
data.frame or tibble with the data, often a subset of data created with group_by() and pick()
- bootReps
integer giving number of bootstrap replications
- conf
numeric value giving width of confidence interval, e.g. .95 (default)
- bootCImethod
string giving method to derive bootstrap CI, minimum two letters 'pe', 'no', 'ba' or 'bc' for percentile, normal, basic or bca
See also
Other bootstrap CI functions:
getBootCICSC()
,
getBootCICorr()
,
getBootCIalpha()
,
getBootCImean()
Examples
if (FALSE) {
### will need tidyverse to run
library(tidyverse)
### create some data
### get replicable data
set.seed(12345)
n <- 120
list(scores = rnorm(n), # Gaussian random base for scores
### now add a grouping variable: help-seeking or not
grp = sample(c("HS", "not"), n, replace = TRUE),
### now add gender
gender = sample(c("F", "M"), n, replace = TRUE)) %>%
as_tibble() %>%
### next add a gender effect nudging women's scores up by .4
mutate(scores = if_else(gender == "F", scores + .4, scores),
### next add the crucial help-seeking effect of 1.1
scores = if_else(grp == "HS", scores + 1.1, scores)) -> tmpDat
#
### have a look at that
tmpDat
#
set.seed(12345) # to get replicable results from the bootstrap
tmpDat %>%
### don't forget to prefix the call with "list(" to tell dplyr
### you are creating list output
### pick(everything()) has replaced cur_data(), verbose but more flexbible
summarise(meanDiff = list(getBootCIgrpMeanDiff(scores ~ grp, pick(everything())))) %>%
### now unnest the list to columns
unnest_wider(meanDiff)
### now an example of how this becomes useful: same but by gender
set.seed(12345) # to get replicable results from the bootstrap
tmpDat %>%
group_by(gender) %>%
### remember the list output again!
summarise(meanDiff = list(getBootCIgrpMeanDiff(scores ~ grp, pick(everything())))) %>%
### remember to unnnest again!
unnest_wider(meanDiff)
}