Compute "Prodromal Psychosis Scale [Youth] (Bother responses): Number missing"
Source:R/scores_mh.R
compute_mh_y_pps__bother_nm.Rd
Computes the summary score mh_y_pps__bother_nm
Prodromal Psychosis Scale [Youth] (Bother responses): Number missing
Summarized variables:
mh_y_pps__bother_001
mh_y_pps__bother_002
mh_y_pps__bother_003
mh_y_pps__bother_004
mh_y_pps__bother_005
mh_y_pps__bother_006
mh_y_pps__bother_007
mh_y_pps__bother_008
mh_y_pps__bother_009
mh_y_pps__bother_010
mh_y_pps__bother_011
mh_y_pps__bother_012
mh_y_pps__bother_013
mh_y_pps__bother_014
mh_y_pps__bother_015
mh_y_pps__bother_016
mh_y_pps__bother_017
mh_y_pps__bother_018
mh_y_pps__bother_019
mh_y_pps__bother_020
mh_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))
)
} # }