Imputation by the mean
Imputes the arithmetic mean of the observed data
mice.impute.mean(y, ry, x = NULL, wy = NULL, ...)
y |
Vector to be imputed |
ry |
Logical vector of length |
x |
Numeric design matrix with |
wy |
Logical vector of length |
... |
Other named arguments. |
Vector with imputed data, same type as y
, and of length
sum(wy)
Imputing the mean of a variable is almost never appropriate. See Little and Rubin (2002, p. 61-62) or Van Buuren (2012, p. 10-11)
Van Buuren, S., Groothuis-Oudshoorn, K. (2011). mice
:
Multivariate Imputation by Chained Equations in R
. Journal of
Statistical Software, 45(3), 1-67.
https://www.jstatsoft.org/v45/i03/
Little, R.J.A. and Rubin, D.B. (2002). Statistical Analysis with Missing Data. New York: John Wiley and Sons.
Van Buuren, S. (2018). Flexible Imputation of Missing Data. Second Edition. Chapman & Hall/CRC. Boca Raton, FL.
Other univariate imputation functions:
mice.impute.cart()
,
mice.impute.lda()
,
mice.impute.logreg.boot()
,
mice.impute.logreg()
,
mice.impute.midastouch()
,
mice.impute.mnar.logreg()
,
mice.impute.norm.boot()
,
mice.impute.norm.nob()
,
mice.impute.norm.predict()
,
mice.impute.norm()
,
mice.impute.pmm()
,
mice.impute.polr()
,
mice.impute.polyreg()
,
mice.impute.quadratic()
,
mice.impute.rf()
,
mice.impute.ri()
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