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Compute "KSADS - Oppositional Defiant Disorder [Parent] (Symptom - Present): Mean"

Source: R/scores_mh.R
compute_mh_p_ksads__odd__pres__sx_mean.Rd

Computes the summary score mh_p_ksads__odd__pres__sx_mean KSADS - Oppositional Defiant Disorder [Parent] (Symptom - Present): Mean [validation: No more than 1 missing or declined]

  • Summarized variables:

    • mh_p_ksads__odd__angry__pres_sx

    • mh_p_ksads__odd__argue__pres_sx

    • mh_p_ksads__odd__blame__pres_sx

    • mh_p_ksads__odd__delibannoy__pres_sx

    • mh_p_ksads__odd__disobey__pres_sx

    • mh_p_ksads__odd__temper__pres_sx

    • mh_p_ksads__odd__touchy__pres_sx

    • mh_p_ksads__odd__vindict__pres_sx

  • Excluded values:

    • 555

  • Validation criterion: maximally 1 of 8 items missing

Usage

vars_mh_p_ksads__odd__pres__sx

compute_mh_p_ksads__odd__pres__sx_mean(
  data,
  name = "mh_p_ksads__odd__pres__sx_mean",
  max_na = 1,
  exclude = c("555"),
  combine = TRUE
)

Format

vars_mh_p_ksads__odd__pres__sx is a character vector of all column names used to compute summary score of mh_p_ksads__odd__pres__sx_mean

Arguments

data

tbl. Data frame containing the columns to be summarized.

name

character. Name of the summary score column.

max_na

numeric, positive whole number. Number of missing items allowed. NULL means no limit.

exclude

character vector. Values to be excluded from the summary score calculation.

combine

logical. If TRUE (default), the summary score is is appended as a new column to the input data frame. If FALSE, the summary score is returned as a separate one-column data frame.

Value

tbl. see combine.

Details

KSADS summary scores are mostly calculating the means over variables, but there are two special codes to handle:

  • "888": item skipped by branching. When at least one input value is observed, any 888 value is converted to "0" prior to averaging.

  • "555": module not administered. If any input variable is "555" leave the score as NA.

  • NA: missing value. If at least one input value is observed, any NA values are converted to "0" prior to averaging. If all inputs are NA, the summary score remains NA.