LogisticReg {TestDataImputation} | R Documentation |
Logistic Regression (LR) Imputation
Description
This function imputes for all missing responses using logistic regression (for binary responses) or polytomous regression (for polytomous responses). The mice () function with default settings from the mice package (Van Buuren & Groothuis-Oudshoorn, 2011 <doi: 10.18637/jss.v045.i03>) is used to impute for the missing responses.
Usage
LogisticReg(test.data, Mvalue = "NA", max.score = 1)
Arguments
test.data |
Test data set (a data frame or a matrix) containing missing responses. Missing values are coded as NA or other values (e.g., 8, 9). |
Mvalue |
Missing response indicators in the data (e.g. "NA", "8", "9", etc.). Mvalue="NA" by default. |
max.score |
The max possible response value in test data. By default max.score=1 (i.e.,binary test data). |
Value
A data frame with all missing responses replaced by integrated imputed values.
References
Van Buuren, S., & Groothuis-Oudshoorn, K. (2011). "mice: Multivariate imputation by chained equations in R." Journal of statistical software, 45(1), 1-67. DOI: 10.18637/jss.v045.i03.
Examples
LogisticReg(test.data, Mvalue="NA",max.score=1)