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mice (version 2.7)

mice.impute.passive: Passive Imputation

Description

Derive a new variable based on the imputed data

Usage

mice.impute.passive(data, func)

Arguments

data
A data frame
func
A formula specifying the transformations on data

Value

  • tThe transformed data

Details

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.

References

Van Buuren, S., Groothuis-Oudshoorn, K. (2010) MICE: Multivariate Imputation by Chained Equations in R. Journal of Statistical Software, forthcoming. http://www.stefvanbuuren.nl/publications/MICE in R - Draft.pdf

See Also

mice