amd_multi: Amount of Missing Data - Multivariate (Listwise Deletion)

In quest: Prepare Questionnaire Data for Analysis

Amount of Missing Data - Multivariate (Listwise Deletion)

Description

amd_multi by default computes the proportion of missing data from listwise deletion for a set of variables in a data.frame, with arguments to allow for counts instead of proportions (i.e., prop) or observed data rather than missing data (i.e., ov). It is multivariate in that the variables are treated together as a set.

Usage

amd_multi(data, vrb.nm, prop = TRUE, ov = FALSE)

Arguments

data	data.frame of data.
vrb.nm	character vector of the colnames from data specifying the variables.
prop	logical vector of length 1 specifying whether the frequency of missing values should be returned as a proportion (TRUE) or a count (FALSE).
ov	logical vector of length 1 specifying whether the frequency of observed values (TRUE) should be returned rather than the frequency of missing values (FALSE).

Value

numeric vector of length 1 providing the frequency of missing (or observed if ov = TRUE) rows from listwise deletion for the set of variables vrb.nm. If prop = TRUE, the value will range from 0 to 1. If prop = FALSE, the value will range from 0 to nrow(data).

See Also

amd_uni amd_bi

Examples

amd_multi(airquality, vrb.nm = names(airquality)) # proportion of missing data
amd_multi(airquality, vrb.nm = names(airquality),
   ov = TRUE) # proportion of observed data
amd_multi(airquality, vrb.nm = names(airquality),
   prop = FALSE) # count of missing data
amd_multi(airquality, vrb.nm = names(airquality),
   prop = FALSE, ov = TRUE) # count of observed data

quest documentation built on May 29, 2024, 4:59 a.m.