Description Usage Arguments Value References
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 2 3 4 5 6 7 8 | imp_roundedcont(
y_df,
X_imp,
PSI,
pvalue = 0.2,
k = Inf,
rounding_degrees = NULL
)
|
y_df |
A data.frame with the variable to impute. |
X_imp |
A data.frame with the fixed effects variables explaining y_df. |
PSI |
A data.frame with the variables explaining the latent rounding tendency G. |
pvalue |
A numeric between 0 and 1 denoting the threshold of p-values a variable in the imputation model should not exceed. If they do, they are excluded from the imputation model. |
k |
An integer defining the allowed maximum of levels in a factor covariate. |
rounding_degrees |
A numeric vector with the presumed rounding degrees for Y. |
A n x 1 data.frame with the original and imputed values.
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
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.