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.
1 2 |
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 \bold{X}'\bold{X} |
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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