R: Combine 'mids' objects by rows

rbind.mids {mice} | R Documentation

## Combine `mids` objects by rows

### Description

This function combines two `mids` objects rowwise into a single `mids` object, or combines a `mids` object with a vector, matrix, factor or dataframe rowwise into a `mids` object.

### Usage

    rbind.mids(x, y = NULL, ...)

### Arguments

`x` | A `mids` object.
`y` | A `mids` object, or a `data.frame`, `matrix`, `factor` or `vector`.
`...` | Additional `data.frame`, `matrix`, `vector` or `factor`. These can be given as named arguments.

### Details

If `y` is a `mids` object, then `rbind` requires that the number of multiple imputations in `x` and `y` is identical. Also, columns of `x$data` and `y$data` should match.

If `y` is not a `mids` object, the columns of `x$data` and `y` should match. The `where` matrix for `y` is set to `FALSE`, signaling that any missing values in `y` were not imputed. The `ignore` vector for `y` is set to `FALSE`, elements of `y` will therefore influence the parameters of the imputation model in future iterations.

### Value

An S3 object of class `mids`

### Note

The function construct the elements of the new `mids` object as follows:

`data` | Rowwise combination of the (incomplete) data in `x` and `y`
`imp` | Equals `rbind(x$imp[[j]], y$imp[[j]])` if `y` is `mids` object; otherwise the data of `y` will be copied
`m` | Equals `x$m`
`where` | Rowwise combination of `where` arguments
`blocks` | Equals `x$blocks`
`call` | Vector, `call[1]` creates `x`, `call[2]` is call to `rbind.mids`
`nmis` | `x$nmis` + `y$nmis`
`method` | Taken from `x$method`
`predictorMatrix` | Taken from `x$predictorMatrix`
`visitSequence` | Taken from `x$visitSequence`
`formulas` | Taken from `x$formulas`
`post` | Taken from `x$post`
`blots` | Taken from `x$blots`
`ignore` | Concatenate `x$ignore` and `y$ignore`
`seed` | Taken from `x$seed`
`iteration` | Taken from `x$iteration`
`lastSeedValue` | Taken from `x$lastSeedValue`
`chainMean` | Set to `NA`
`chainVar` | Set to `NA`
`loggedEvents` | Taken from `x$loggedEvents`
`version` | Taken from `x$version`
`date` | Taken from `x$date`

### Author(s)

Karin Groothuis-Oudshoorn, Stef van Buuren

### References

van Buuren S and 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

`cbind.mids`, `ibind`, `mids`

### Examples

    imp1 <- mice(nhanes[1:13, ], m = 2, maxit = 1, print = FALSE)
    imp5 <- mice(nhanes[1:13, ], m = 2, maxit = 2, print = FALSE)
    mylist <- list(age = NA, bmi = NA, hyp = NA, chl = NA)

    nrow(complete(rbind(imp1, imp5)))
    nrow(complete(rbind(imp1, mylist)))

    nrow(complete(rbind(imp1, data.frame(mylist))))
    nrow(complete(rbind(imp1, complete(imp5))))

[Package mice version 3.12.0 Index]