mice.impute.norm.boot.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mice.impute.norm.boot.R
\name{mice.impute.norm.boot}
\alias{mice.impute.norm.boot}
\alias{norm.boot}
\title{Imputation by linear regression, bootstrap method}
\usage{
mice.impute.norm.boot(y, ry, x, wy = NULL, ...)
}
\arguments{
\item{y}{Vector to be imputed}

\item{ry}{Logical vector of length \code{length(y)} indicating the
the subset \code{y[ry]} of elements in \code{y} to which the imputation
model is fitted. The \code{ry} generally distinguishes the observed
(\code{TRUE}) and missing values (\code{FALSE}) in \code{y}.}

\item{x}{Numeric design matrix with \code{length(y)} rows with predictors for
\code{y}. Matrix \code{x} may have no missing values.}

\item{wy}{Logical vector of length \code{length(y)}. A \code{TRUE} value
indicates locations in \code{y} for which imputations are created.}

\item{...}{Other named arguments.}
}
\value{
Vector with imputed data, same type as \code{y}, and of length
\code{sum(wy)}
}
\description{
Imputes univariate missing data using linear regression with bootstrap
}
\details{
Draws a bootstrap sample from \code{x[ry,]} and \code{y[ry]}, calculates
regression weights and imputes with normal residuals.
}
\references{
Van Buuren, S., Groothuis-Oudshoorn, K. (2011). \code{mice}:
Multivariate Imputation by Chained Equations in \code{R}. \emph{Journal of
Statistical Software}, \bold{45}(3), 1-67.
\doi{10.18637/jss.v045.i03}
}
\seealso{
Other univariate imputation functions: 
\code{\link{mice.impute.cart}()},
\code{\link{mice.impute.lasso.logreg}()},
\code{\link{mice.impute.lasso.norm}()},
\code{\link{mice.impute.lasso.select.logreg}()},
\code{\link{mice.impute.lasso.select.norm}()},
\code{\link{mice.impute.lda}()},
\code{\link{mice.impute.logreg}()},
\code{\link{mice.impute.logreg.boot}()},
\code{\link{mice.impute.mean}()},
\code{\link{mice.impute.midastouch}()},
\code{\link{mice.impute.mnar.logreg}()},
\code{\link{mice.impute.mpmm}()},
\code{\link{mice.impute.norm}()},
\code{\link{mice.impute.norm.nob}()},
\code{\link{mice.impute.norm.predict}()},
\code{\link{mice.impute.pmm}()},
\code{\link{mice.impute.polr}()},
\code{\link{mice.impute.polyreg}()},
\code{\link{mice.impute.quadratic}()},
\code{\link{mice.impute.rf}()},
\code{\link{mice.impute.ri}()}
}
\author{
Gerko Vink, Stef van Buuren, 2018
}
\concept{univariate imputation functions}
\keyword{datagen}