mice (version 3.16.0)

md.pairs: Missing data pattern by variable pairs

Description

Number of observations per variable pair.

Usage

md.pairs(data)

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.

Arguments

data

A data frame or a matrix containing the incomplete data. Missing values are coded as NA.

Author

Stef van Buuren, Karin Groothuis-Oudshoorn, 2009

Details

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

list('rr')

response-response, both variables are observed

list('rm')

response-missing, row observed, column missing

list('mr')

missing -response, row missing, column observed

list('mm')

missing -missing, both variables are missing

References

Van Buuren, S., Groothuis-Oudshoorn, K. (2011). mice: Multivariate Imputation by Chained Equations in R. Journal of Statistical Software, 45(3), 1-67. tools:::Rd_expr_doi("10.18637/jss.v045.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))