vars_su_y_cigexp__neg: Compute "Cigarette Expectancies (ASCQ) [Youth] (Strength of negative expectancies): Prorated sum"

Description

Computes the summary score su_y_cigexp__neg_prsum Cigarette Expectancies (ASCQ) [Youth] (Strength of negative expectancies): Prorated sum [Validation: No more than 0 missing or declined]

Note: all 0s are changed to NAs prior to calculating pro-rated sum

Summarized variables:
- su_y_cigexp__neg_001
- su_y_cigexp__neg_002
Excluded values:
- 0
Validation criterion: maximally 0 of 2 items missing

Usage

vars_su_y_cigexp__neg
compute_su_y_cigexp__neg_prsum(
  data,
  name = "su_y_cigexp__neg_prsum",
  combine = TRUE,
  exclude = c("0"),
  max_na = 0
)

Value

tbl. The input data frame with the summary score appended as a new column.

Format

vars_su_y_cigexp__neg is a character vector of all column names used to compute summary score of su_y_cigexp__neg_prsum and su_y_cigexp__neg_nm.

Arguments

data: tbl. Data frame 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 (default), the summary score will be appended to the input data frame. If FALSE, the summary score for each participant will be returned as a separate data frame. (Default: TRUE)
exclude: character vector. Values to be excluded from the summary score calculation.
max_na: numeric, positive whole number. Number of missing items allowed (Default: 1).