R Graphical Manual

Last data update: 2014.03.03

R: Imputation by a Weighted Linear Normal Regression

mice.impute.weighted.norm

R Documentation

Imputation by a Weighted Linear Normal Regression

Imputation by a weighted linear normal regression.

mice.impute.weighted.norm(y, ry, x, ridge = 1e-05, pls.facs = NULL, 
     imputationWeights = NULL, interactions = NULL, quadratics = NULL, ...)

`y`	Incomplete data vector of length `n`
`ry`	Vector of missing data pattern (`FALSE` – missing, `TRUE` – observed)
`x`	Matrix (`n` x `p`) of complete covariates.
`ridge`	Ridge parameter in the diagonal of old{X}'old{X}
`imputationWeights`	Optional vector of sampling weights
`pls.facs`	Number of factors in PLS regression (if used). The default is `NULL` which means that no PLS regression is used for dimension reduction.
`interactions`	Optional vector of variables for which interactions should be created
`quadratics`	Optional vector of variables which should also be included as quadratic effects.
`...`	Further arguments to be passed

A vector of length nmis=sum(!ry) with imputed values.

Alexander Robitzsch