R: Multivariate Imputation by Chained Equations (Iteration Step)

mice.mids {mice} | R Documentation

## Multivariate Imputation by Chained Equations (Iteration Step)

### Description

Takes a `mids` object, and produces a new object of class `mids`.

### Usage

    mice.mids(obj, newdata = NULL, maxit = 1, printFlag = TRUE, ...)

### Arguments

`obj` | An object of class `mids`, typically produces by a previous call to `mice()` or `mice.mids()`
`newdata` | An optional `data.frame` for which multiple imputations are generated according to the model in `obj`.
`maxit` | The number of additional Gibbs sampling iterations.
`printFlag` | A Boolean flag. If `TRUE`, diagnostic information during the Gibbs sampling iterations will be written to the command window. The default is `TRUE`.
`...` | Named arguments that are passed down to the univariate imputation functions.

### Details

This function enables the user to split up the computations of the Gibbs sampler into smaller parts. This is useful for the following reasons:

- RAM memory may become easily exhausted if the number of iterations is large. Returning to prompt/session level may alleviate these problems.

- The user can compute customized convergence statistics at specific points, e.g. after each iteration, for monitoring convergence. - For computing a 'few extra iterations'.

Note: The imputation model itself is specified in the `mice()` function and cannot be changed with `mice.mids`. The state of the random generator is saved with the `mids` object.

### Author(s)

Stef van Buuren, Karin Groothuis-Oudshoorn, 2000

### References

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

### See Also

`complete`, `mice`, `set.seed`, `mids`

### Examples

    imp1 <- mice(nhanes, maxit = 1, seed = 123)
    imp2 <- mice.mids(imp1)

    # yields the same result as
    imp <- mice(nhanes, maxit = 2, seed = 123)

    # verification
    identical(imp$imp, imp2$imp)
    #

[Package mice version 3.12.0 Index]