Pools R^2 of m models fitted to multiply-imputed data
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.
pool.r.squared(object, adjusted = FALSE)
object |
An object of class 'mira' or 'mipo', produced by |
adjusted |
A logical value. If adjusted=TRUE then the adjusted R^2 is calculated. The default value is FALSE. |
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.
Karin Groothuis-Oudshoorn and Stef van Buuren, 2009
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. https://www.jstatsoft.org/v45/i03/
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)
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