mi (version 0.10-2)

mi.fixed: Elementary function: imputation of constant variable.

Description

Imputes univariate constant missing data.

Usage

mi.fixed( formula, data = NULL, missing.index = NULL, ... )
 mi.copy(Y, X, missing.index = NULL, ...)

Arguments

formula

an object of class '"formula"' (or one that can be coerced to that class): a symbolic description of the model to be fitted. See bayesglm 'formula' for details.

data

A data frame containing the incomplete data and the matrix of the complete predictors.

missing.index

The index of missing units of the outcome variable

Y

A variable that is collinear with X

X

A variable that is colliear with Y

...

Currently not used

Value

• model
  A summary of the fitted model.
• expected
  The expected values estimated by the model.
• random
  Vector of length n.mis of random predicted values predicted by using the normal distribution.

References

Andrew Gelman and Jennifer Hill, Data Analysis Using Regression and Multilevel/Hierarchical Models, Cambridge University Press, 2006.

See Also

mi.info, mi.method, mi

Examples

# fake data
n <- 100
x1 <- rbinom(n, 1, .45)
x2 <- 2*x1
x1[c(1, 3, 5, 20, 26)] <- NA

# impute data
mi.copy(x1, x2)