Missing data pattern by variable pairs

Description

Number of observations per variable pair.

Usage

md.pairs(data)

Arguments

Details

The four components in the output value is have the following interpretation:

rr

response-response, both variables are observed

rm

response-missing, row observed, column missing

mr

missing -response, row missing, column observed

mm

missing -missing, both variables are missing

Value

A list of four components named rr, rm, mr and mm. Each component is square numerical matrix containing the number observations within four missing data pattern.

Author(s)

Stef van Buuren, Karin Groothuis-Oudshoorn, 2009

References

Van Buuren, S., Groothuis-Oudshoorn, K. (2011). mice: Multivariate Imputation by Chained Equations in R. Journal of Statistical Software, 45(3), 1-67. http://www.jstatsoft.org/v45/i03/

Examples

pat <- md.pairs(nhanes)
pat

# show that these four matrices decompose the total sample size
# for each pair
pat$rr + pat$rm + pat$mr + pat$mm

# percentage of usable cases to impute row variable from column variable
round(100*pat$mr/(pat$mr+pat$mm))