mice.impute.weighted.norm: Imputation by a Weighted Linear Normal Regression

Description Usage Arguments Value Author(s) See Also

View source: R/mice.impute.weighted.norm.R

Description

Imputation by a weighted linear normal regression.

Usage

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

Arguments

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 \bold{X}'\bold{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

Value

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

Author(s)

Alexander Robitzsch

See Also

For examples see mice.impute.weighted.pmm


miceadds documentation built on Aug. 25, 2017, 1:03 a.m.