This imputation method imputes a variable using linear regression with normally distributed residuals. Including a contextual effects means that an aggregated variable at a cluster level is included as a further covariate.

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`y` |
Incomplete data vector of length |

`ry` |
Vector of missing data pattern ( |

`x` |
Matrix ( |

`type` |
Type of predictor variables. |

`ridge` |
Ridge parameter in the diagonal of |

`imputationWeights` |
Optional vector of sample weights |

`interactions` |
Vector of variable names used for creating interactions |

`quadratics` |
Vector of variable names used for creating quadratic terms |

`...` |
Further arguments to be passed |

A vector of length `nmis=sum(!ry)`

with imputed values.

Alexander Robitzsch

For examples see `mice.impute.2l.contextual.pmm`

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