mice (version 2.2)

mice.impute.norm.predict: Imputation by linear regression, prediction method

Description

Imputes univariate missing data using the predicted value from a linear regression

Usage

mice.impute.norm.predict(y, ry, x, ridge = 1e-05, ...)

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

...

Other named arguments.

Value

• A vector of length nmis with imputations.

Details

Calculates regression weights from the observed data and and return predicted values to as imputations. The ridge parameter adds a penalty term ridge*diag(xtx) to the variance-covariance matrix xtx.

References

Van Buuren, S., Groothuis-Oudshoorn, K. (2011). mice: Multivariate Imputation by Chained Equations in R. Journal of Statistical Software, 45(3), 1-67. http://www.jstatsoft.org/v45/i03/