Description Details Author(s) See Also Examples

Contains some auxiliary functions for multiple
imputation which complements existing functionality
in **R**.
In addition to some utility functions, main features
include plausible value imputation, multilevel
imputation functions (arbitrary number of levels,
hierarchical and non-hierarchical datasets),
imputation using partial least squares (PLS) for
high dimensional predictors, and nested multiple
imputation.

The miceadds package contains some functionality for imputation of multilevel data. The function

`mice.impute.ml.lmer`

is a general function for imputing multilevel data with hierarchical or cross-classified structures for variables at an arbitrary level. This imputation method uses the`lme4::lmer`

function in the lme4 package. The imputation method`mice.impute.2lonly.function`

conducts an imputation for a variable at a higher level for already defined imputation methods in the mice package. Two-level imputation is available in several functions in the mice package (`mice::mice.impute.2l.pan`

,`mice::mice.impute.2l.norm`

) as well in micemd and hmi packages. The miceadds package contains additional imputation methods for two-level datasets:`mice.impute.2l.continuous`

for normally distributed data,`mice.impute.2l.pmm`

for predictive mean matching in multilevel models and`mice.impute.2l.binary`

for binary data.In addition to the usual

`mice`

imputation function which employs parallel chains, the function`mice.1chain`

does multiple imputation from a single chain.Nested multiple imputation can be conducted with

`mice.nmi`

. The function`NMIcombine`

conducts statistical inference for nested multiply imputed datasets.Imputation based on partial least squares regression is implemented in

`mice.impute.pls`

.Unidimensional plausible value imputation for latent variables (or variables with measurement error) in the mice sequential imputation framework can be applied by using the method

`mice.impute.plausible.values`

.The miceadds package also includes some functions

**R**utility functions (e.g.`write.pspp`

,`ma.scale2`

).Imputations for questionnaire items can be accomplished by two-way imputation (

`tw.imputation`

).

Alexander Robitzsch, Simon Grund, Thorsten Henke

Maintainer: Alexander Robitzsch <[email protected]>

See other **R** packages for conducting multiple imputation:
mice, Amelia, pan, mi, norm,
norm2, BaBooN, VIM, ...

Some links to internet sites related to missing data:

http://missingdata.lshtm.ac.uk/

http://www.stefvanbuuren.nl/mi/

http://www.bristol.ac.uk/cmm/software/realcom/

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``` |

```
Loading required package: mice
* miceadds 2.7-19 (2017-08-24 17:34:44)
```

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