Imputation | R Documentation |
Imputation
This is a wrapper for mice
.
Imputation(
data = NULL,
formula = NULL,
method = "try mice",
m = 1,
seed = 12321
)
data |
A |
formula |
A |
method |
"mice" applies multivariate imputation by chained equations
(predictive mean matching) with the |
m |
Number of imputation samples. |
seed |
Seed used in random number generation. |
Variables with class "POSIXct"
are converted to numeric and
scaled prior to imputation. Variables with class "character"
are converted
to factor prior to imputation with blank (0-character) entries considered missing.
von Hippel, Paul T. 2007. "Regression With Missing Y's: An Improved Strategy for Analyzing Multiply Imputed Data." Sociological Methodology 37:83-117. Skyler J. Cranmer and Jeff Gill (2013). We Have to Be Discrete About This: A Non-Parametric Imputation Technique for Missing Categorical Data. British Journal of Political Science, 43, pp 425-449. Stef van Buuren and Karin Groothuis-Oudshoorn (2011), "mice: Multivariate Imputation by Chained Equations in R", Journal of Statistical Software, 45:3, 1-67.
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