Description Usage Arguments Value References
View source: R/hmi_imp_roundedcont_2018-05-11.R View source: R/hmi_imp_roundedcont_2018-05-04.R View source: R/hmi_imp_roundedcont_2018-02-23.R View source: R/hmi_imp_roundedcont_2018-02-08.R View source: R/hmi_imp_roundedcont_2018-01-26b.R View source: R/hmi_imp_roundedcont_2018-01-11.R View source: R/hmi_imp_roundedcont_2017-12-27.R View source: R/hmi_imp_roundedcont_2017-10-18.R View source: R/hmi_imp_roundedcont_2017-09-01.R View source: R/hmi_imp_roundedcont_2017-01-31.R View source: R/hmi_imp_roundedcont_2017-01-05.R View source: R/hmi_imp_roundedcont_2016-12-16.R View source: R/hmi_imp_roundedcont_2016-12-09.R View source: R/hmi_imp_roundedcont.R
For example the income in surveys is often reported rounded by the respondents. See Drechsler, Kiesl and Speidel (2015) for more details.
1 | imp_roundedcont(y_imp_multi, X_imp_multi, intercept_varname = NULL, M)
|
y_imp_multi |
A Vector with the variable to impute. |
X_imp_multi |
A data.frame with the fixed effects variables. |
intercept_varname |
A character denoting the name of the intercept variable. |
M |
An integer defining the number of imputations that should be made. |
A n x M matrix. Each column is one of M imputed y-variables.
Joerg Drechsler, Hans Kiesl, Matthias Speidel (2015): "MI Double Feature: Multiple Imputation to Address Nonresponse and Rounding Errors in Income Questions". Austrian Journal of Statistics Vol. 44, No. 2, http://dx.doi.org/10.17713/ajs.v44i2.77
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