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mice (version 1.14)

impute.passive: Elementary Imputation Method: Passive Imputation

Description

Derive a new variable based on the imputed data

Usage

impute.passive(data, func)

Arguments

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

Value

  • tThe tranformed data.

Details

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 $(x1+x2+x3)/3$. 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. & Oudshoorn, C.G.M. (2000). Multivariate Imputation by Chained Equations: MICE V1.0 User's manual. Report PG/VGZ/00.038, TNO Prevention and Health, Leiden.

See Also

mice