MISSING_INFO: Missing value statistics

In EFA.dimensions: Exploratory Factor Analysis Functions for Assessing Dimensionality

Missing value statistics

Description

Frequencies and proportions of missing values

Usage

MISSING_INFO(data, verbose)

Arguments

data	An all-numeric dataframe where the rows are cases & the columns are the variables.
verbose	(optional) Should detailed results be displayed in console? TRUE (default) or FALSE

Details

Provides the number of cases with each of N missing values (NA values), along with the proportions, cumulative proportions, and the cumulative Ns.

Value

A matrix with the following columns:

N_cases	The number of cases
N_missing	The number of missing values
Proportion	The proportion of missing values
Cum_Proportion	The cumulative proportion of missing values
Cum_N	The cumulative number of cases

Author(s)

Brian P. O'Connor

Examples

MISSING_INFO(airquality)

# add NA values to the Rosenberg Self-Esteem scale items, for illustration
data_RSE_missing <- data_RSE
data_RSE_missing[matrix(rbinom(prod(dim(data_RSE_missing)), size=1, prob=.3)==1, 
                 nrow=dim(data_RSE_missing)[1])] <- NA

MISSING_INFO(data_RSE_missing)

EFA.dimensions documentation built on June 22, 2024, 10:18 a.m.