mice.impute.passive {mice} | R Documentation |
Derive a new variable based on the imputed data
mice.impute.passive(data, func)
data |
A data frame |
func |
A |
Passive imputation is a special internal imputation function.
Using this facility, the user can specify, at any point in the mice
Gibbs sampling algorithm, a function on the imputed data.
This is useful, for example, to compute a cubic version
of a variable, a transformation like Q = W/H^2
based on two variables,
or a mean variable like (x_1+x_2+x_3)/3
. The so derived variables might be
used in other places in the imputation model.
The function allows to dynamically derive virtually any function
of the imputed data at virtually any time.
t |
The transformed data |
Stef van Buuren, Karin Groothuis-Oudshoorn, 2000
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/