Compute "Early Adolescent Temperament Questionnaire [Parent] (Surgency): Mean [Validation: No more than 1 missing or declined]"
Source:R/scores_mh.R
compute_mh_p_eatq__surg_mean.RdComputes the summary score mh_p_eatq__surg_mean
Early Adolescent Temperament Questionnaire [Parent] (Surgency): Mean
[Validation: No more than 1 missing or declined]
Summarized variables:
mh_p_eatq__surg_001mh_p_eatq__surg_002mh_p_eatq__surg_003mh_p_eatq__surg_004mh_p_eatq__surg_005mh_p_eatq__surg_006mh_p_eatq__surg_007mh_p_eatq__surg_008mh_p_eatq__surg_009
Excluded values: none
Validation criterion: maximally 1 of 9 items missing
Usage
vars_mh_p_eatq__surg
compute_mh_p_eatq__surg_mean(
data,
name = "mh_p_eatq__surg_mean",
max_na = 1,
combine = TRUE,
revert = FALSE
)Format
vars_mh_p_eatq__surg is a character vector of all column names
used to compute summary score of mh_p_eatq__surg_mean.
Arguments
- data
tbl, Dataframe containing the columns to be summarized.
- name
character, Name of the new column to be created. Default is the name in description, but users can change it.
- max_na
integer, Maximum number of missing values allowed in the summary score.
NULLmeans no limit.- combine
logical, If
TRUE, the summary score will be appended to the input data frame. IfFALSE, the summary score will be returned as a separate data frame.- revert
logical, If
TRUE, the summary score will be reverse scored.
Examples
if (FALSE) { # \dontrun{
data <- compute_mh_p_eatq__surg_mean(data)
select(
data,
any_of(c("mh_p_eatq__surg_mean", vars_mh_p_eatq__surg))
)
} # }