Compute "Prodromal Psychosis Scale [Youth] (Bother responses): Number missing"
Source:R/scores_mh.R
compute_mh_y_pps__bother_nm.RdComputes the summary score mh_y_pps__bother_nm
Prodromal Psychosis Scale [Youth] (Bother responses): Number missing
Summarized variables:
mh_y_pps__bother_001mh_y_pps__bother_002mh_y_pps__bother_003mh_y_pps__bother_004mh_y_pps__bother_005mh_y_pps__bother_006mh_y_pps__bother_007mh_y_pps__bother_008mh_y_pps__bother_009mh_y_pps__bother_010mh_y_pps__bother_011mh_y_pps__bother_012mh_y_pps__bother_013mh_y_pps__bother_014mh_y_pps__bother_015mh_y_pps__bother_016mh_y_pps__bother_017mh_y_pps__bother_018mh_y_pps__bother_019mh_y_pps__bother_020mh_y_pps__bother_021
Usage
vars_mh_y_pps__bother
compute_mh_y_pps__bother_nm(data, name = "mh_y_pps__bother_nm", combine = TRUE)Format
vars_mh_y_pps__bother is a character vector of all
column names used to compute summary of mh_y_pps__bother scores.
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.
- 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.
Details
The number of missing values in the mh_y_pps__bother score is
calculated by subtracting the number of valid pairs from the total
PPS count for each subject (mh_y_pps_count - bother_pair_good_sum).
A good pair is defined as a pair where the mh_y_pps_count is 1 and
the mh_y_pps__bother is not missing.
Examples
if (FALSE) { # \dontrun{
compute_mh_y_pps__bother_nm(data) |>
select(
any_of(c("mh_y_pps__bother_nm", vars_mh_y_pps__bother))
)
} # }