mice.impute.ri

Incomplete data vector of length <code>n</code>

Vector of missing data pattern
  (<code>FALSE</code>=missing, <code>TRUE</code>=observed)

Matrix (<code>n</code> x <code>p</code>) of complete
  covariates.

ri.maxit

Other named arguments passed down to
  <code>.norm.draw()</code>

Imputes univariate missing data using the random
  indicator method. This method estimates an offset between
  the distribution of the observed and missing data using
  an algorithm that iterates over the response model and
  the imputation model.

datagen

Multiple Imputation using Fully Conditional Specification

mice.impute.ri: Imputation by the random indicator method for nonignorable data

Description

Usage

Arguments

Value

References