smind: Structural missingness indicator

In sdap: Statistical Data Preparation Indicators

Description

Structurally missingness indicator creates a matrix bij which contains the structural missingness indicator for each element of a filtered variable group.

Usage

smind(data, filtering_var, filtered_var, filter_values, positive = 0, bij)

Arguments

data	(mandatory): A dataframe containing the data to be processed.
filtering_var	(mandatory): Column numbers of the variables which determine the filter.
filtered_var	(mandatory): Column numbers of the variables which are filtered.
filter_values	(mandatory): Values to be checked against the filtering variables. e.g. c("",NA,1,-1, -2).
positive	(optional): When positive = 0 (default) the filtered variables are considered structurally missing if all of the filtering variables have a value among the filter values. When positive = 1, the filtered variables are considered structurally missing if any of the filtered variables has a value among the filter values.
bij	(optional): A preexisting structural missingness indicator matrix.

Value

A matrix bij which contains the missingness indicator for each element of the filtered variables, given a list of filtering variables and a list of filtered variables, as well as a list of structurally missingness elements.

Author(s)

Beat Hulliger, Juan Berdugo

sdap documentation built on May 2, 2019, 6:52 p.m.