mice (version 3.15.0)

pool.r.squared: Pools R^2 of m models fitted to multiply-imputed data

Description

The function pools the coefficients of determination R^2 or the adjusted coefficients of determination (R^2_a) obtained with the lm modeling function. For pooling it uses the Fisher z-transformation.

Usage

pool.r.squared(object, adjusted = FALSE)

Value

Returns a 1x4 table with components. Component est is the pooled R^2 estimate. Component lo95 is the 95 % lower bound of the pooled R^2. Component hi95 is the 95 % upper bound of the pooled R^2. Component fmi is the fraction of missing information due to nonresponse.

Arguments

object

An object of class 'mira' or 'mipo', produced by lm.mids, with.mids, or pool with lm as modeling function.

adjusted

A logical value. If adjusted=TRUE then the adjusted R^2 is calculated. The default value is FALSE.

Author

Karin Groothuis-Oudshoorn and Stef van Buuren, 2009

References

Harel, O (2009). The estimation of R^2 and adjusted R^2 in incomplete data sets using multiple imputation, Journal of Applied Statistics, 36:1109-1118.

Rubin, D.B. (1987). Multiple Imputation for Nonresponse in Surveys. New York: John Wiley and Sons.

van Buuren S and 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")

See Also

pool,pool.scalar

Examples

imp <- mice(nhanes, print = FALSE, seed = 16117)
fit <- with(imp, lm(chl ~ age + hyp + bmi))

# input: mira object
pool.r.squared(fit)
pool.r.squared(fit, adjusted = TRUE)

# input: mipo object
est <- pool(fit)
pool.r.squared(est)
pool.r.squared(est, adjusted = TRUE)