util_combine_missing_lists: Combine missing-lists for a set of variables to be displayed in the same heat-map

Description

Combine missing-lists for a set of variables to be displayed in the same heat-map

Usage

util_combine_missing_lists(
  resp_vars,
  study_data,
  meta_data,
  label_col,
  include_sysmiss,
  cause_label_df,
  assume_consistent_codes = TRUE,
  expand_codes = assume_consistent_codes,
  suppressWarnings = FALSE
)

Value

a list with:

ModifiedStudyData: data frame with re-coded (if needed) study data
cause_label_df: data frame with re-coded missing codes suitable for all variables

Arguments

resp_vars: variable list the name of the measurement variables
study_data: data.frame the data frame that contains the measurements
meta_data: data.frame the data frame that contains metadata attributes of study data
label_col: variable attribute the name of the column in the metadata with labels of variables
include_sysmiss: logical Optional, if TRUE system missingness (NAs) is evaluated in the summary plot
cause_label_df: data.frame missing code table. If missing codes have labels the respective data frame can be specified here, see cause_label_df
assume_consistent_codes: logical if TRUE and no labels are given and the same missing/jump code is used for more than one variable, the labels assigned for this code will be the same for all variables.
expand_codes: logical if TRUE, code labels are copied from other variables, if the code is the same and the label is set somewhere
suppressWarnings: logical warn about consistency issues with missing and jump lists