Functions to impute using Random Forest under Full Conditional Specifications (Multivariate Imputation by Chained Equations). The CALIBER programme is funded by the Wellcome Trust (086091/Z/08/Z) and the National Institute for Health Research (NIHR) under its Programme Grants for Applied Research programme (RP-PG-0407-10314). The author is supported by a Wellcome Trust Clinical Research Training Fellowship (0938/30/Z/10/Z).
|Author||Anoop Shah [aut, cre], Jonathan Bartlett [ctb], Harry Hemingway [ths], Owen Nicholas [ths], Aroon Hingorani [ths]|
|Date of publication||2014-10-23 13:03:21|
|Maintainer||Anoop Shah <email@example.com>|
CALIBERrfimpute-package: Imputation in MICE using Random Forest
makemar: Creates artificial missing at random missingness
mice.impute.rfcat: Impute categorical variables using Random Forest within MICE
mice.impute.rfcont: Impute continuous variables using Random Forest within MICE
setRFoptions: Set Random Forest options for imputation using MICE
simdata: Simulate multivariate data for testing
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