vars_mh_y_pps__bother | R Documentation |
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
vars_mh_y_pps__bother
compute_mh_y_pps__bother_nm(data, name = "mh_y_pps__bother_nm", combine = TRUE)
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 |
vars_mh_y_pps__bother is a character vector of all
column names used to compute summary of mh_y_pps__bother
scores.
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.
compute_mh_y_pps_count()
## Not run:
compute_mh_y_pps__bother_nm(data) |>
select(
any_of(c("mh_y_pps__bother_nm", vars_mh_y_pps__bother))
)
## End(Not run)
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