imp_orderedcat_single: The function to impute ordered categorical variables
In matthiasspeidel/hmi: Hierarchical Multiple Imputation
Description
Usage
Arguments
Value
View source: R/hmi_imp_catordered_single_2018-04-17.R
View source: R/hmi_imp_catordered_single_2018-02-23.R
View source: R/hmi_imp_catordered_single_2018-02-05.R
View source: R/hmi_imp_catordered_single_2017-08-02.R
View source: R/hmi_imp_catordered_single_2016-12-22.R
View source: R/hmi_imp_catordered_single.R
Description
The function uses the proportional odds logistic regression (polr) approach,
implemented in mice.
Usage
1
imp_orderedcat_single(y_imp_multi, X_imp_multi)
Arguments
y_imp_multi
A Vector with the variable to impute.
X_imp_multi
A data.frame with the fixed effects variables.
Value
A n x 1 matrix.
matthiasspeidel/hmi documentation built on Aug. 18, 2020, 4:37 p.m.
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Description Usage Arguments Value
View source: R/hmi_imp_catordered_single_2018-04-17.R View source: R/hmi_imp_catordered_single_2018-02-23.R View source: R/hmi_imp_catordered_single_2018-02-05.R View source: R/hmi_imp_catordered_single_2017-08-02.R View source: R/hmi_imp_catordered_single_2016-12-22.R View source: R/hmi_imp_catordered_single.R
Description
The function uses the proportional odds logistic regression (polr) approach,
implemented in mice.
Usage
1 | imp_orderedcat_single(y_imp_multi, X_imp_multi)
|
Arguments
y_imp_multi |
A Vector with the variable to impute. |
X_imp_multi |
A data.frame with the fixed effects variables. |
Value
A n x 1 matrix.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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