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 formula specifying the transformations on data |
This is a special imputation function for so-called passive imputation.
Using this function, 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 tranformed data. |
Stef van Buuren, Karin Groothuis-Oudshoorn, 2000
Van Buuren, S., Groothuis-Oudshoorn, C.G.M. (2000) Multivariate Imputation by Chained Equations: MICE V1.0 User's manual. Leiden: TNO Quality of Life. http://www.stefvanbuuren.nl/publications/MICE V1.0 Manual TNO00038 2000.pdf