Imputes univariate missing data using the predicted value from a linear regression
mice.impute.norm.predict(y, ry, x, ridge = 1e-05, ...)
Incomplete data vector of length n
Vector of missing data pattern (FALSE
=missing,
TRUE
=observed)
Matrix (n
x p
) of complete covariates.
Ridge parameter
Other named arguments.
A vector of length nmis
with imputations.
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
.
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/