Description Usage Arguments Details Value Note Author(s) See Also Examples

This function combines two `mids`

objects columnwise into a single
object of class `mids`

, or combines a single `mids`

object with
a `vector`

, `matrix`

, `factor`

or `data.frame`

columnwise into a `mids`

object.

1 | ```
cbind.mids(x, y = NULL, ...)
``` |

`x` |
A |

`y` |
A |

`...` |
Additional |

*Pre-requisites:* If `y`

is a `mids`

-object, the rows
of `x$data`

and `y$data`

should match, as well as the number
of imputations (`m`

). Other `y`

are transformed into a
`data.frame`

whose rows should match with `x$data`

.

The function renames any duplicated variable or block names by
appending `".1"`

, `".2"`

to duplicated names.

An S3 object of class `mids`

The function constructs the elements of the new `mids`

object as follows:

`data` | Columnwise combination of the data in `x` and `y` |

`imp` | Combines the imputed values from `x` and `y` |

`m` | Taken from `x$m` |

`where` | Columnwise combination of `x$where` and `y$where` |

`blocks` | Combines `x$blocks` and `y$blocks` |

`call` | Vector, `call[1]` creates `x` , `call[2]`
is call to `cbind.mids` |

`nmis` | Equals `c(x$nmis, y$nmis)` |

`method` | Combines `x$method` and `y$method` |

`predictorMatrix` | Combination with zeroes on the off-diagonal blocks |

`visitSequence` | Combined as `c(x$visitSequence, y$visitSequence)` |

`formulas` | Combined as `c(x$formulas, y$formulas)` |

`post` | Combined as `c(x$post, y$post)` |

`blots` | Combined as `c(x$blots, y$blots)` |

`ignore` | Taken from `x$ignore` |

`seed` | Taken from `x$seed` |

`iteration` | Taken from `x$iteration` |

`lastSeedValue` | Taken from `x$lastSeedValue` |

`chainMean` | Combined from `x$chainMean` and `y$chainMean` |

`chainVar` | Combined from `x$chainVar` and `y$chainVar` |

`loggedEvents` | Taken from `x$loggedEvents` |

`version` | Current package version |

`date` | Current date |

Karin Groothuis-Oudshoorn, Stef van Buuren

`cbind`

, `rbind.mids`

, `ibind`

,
`mids`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | ```
# impute four variables at once (default)
imp <- mice(nhanes, m = 1, maxit = 1, print = FALSE)
imp$predictorMatrix
# impute two by two
data1 <- nhanes[, c("age", "bmi")]
data2 <- nhanes[, c("hyp", "chl")]
imp1 <- mice(data1, m = 2, maxit = 1, print = FALSE)
imp2 <- mice(data2, m = 2, maxit = 1, print = FALSE)
# Append two solutions
imp12 <- cbind(imp1, imp2)
# This is a different imputation model
imp12$predictorMatrix
# Append the other way around
imp21 <- cbind(imp2, imp1)
imp21$predictorMatrix
# Append 'forgotten' variable chl
data3 <- nhanes[, 1:3]
imp3 <- mice(data3, maxit = 1, m = 2, print = FALSE)
imp4 <- cbind(imp3, chl = nhanes$chl)
# Of course, chl was not imputed
head(complete(imp4))
# Combine mids object with data frame
imp5 <- cbind(imp3, nhanes2)
head(complete(imp5))
``` |

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