mice2: Function for multiple imputation by chained equations...
In moreno-betancur/survtd: Survival analysis with time-dependent covariates
Description
Modified version of mice function from the mice package to allow for "lmm" imputation method.
Usage
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mice2(data, m = 5, method = vector("character", length = ncol(data)),
predictorMatrix = (1 - diag(1, ncol(data))),
visitSequence = (1:ncol(data))[apply(is.na(data), 2, any)],
form = vector("character", length = ncol(data)),
post = vector("character", length = ncol(data)), defaultMethod = c("pmm",
"logreg", "polyreg", "polr"), maxit = 5, diagnostics = TRUE,
printFlag = TRUE, seed = NA, imputationMethod = NULL,
defaultImputationMethod = NULL, data.init = NULL, ...)
moreno-betancur/survtd documentation built on May 20, 2019, 5:07 p.m.
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Description
Modified version of mice function from the mice package to allow for "lmm" imputation method.
Usage
1 2 3 4 5 6 7 8 | mice2(data, m = 5, method = vector("character", length = ncol(data)),
predictorMatrix = (1 - diag(1, ncol(data))),
visitSequence = (1:ncol(data))[apply(is.na(data), 2, any)],
form = vector("character", length = ncol(data)),
post = vector("character", length = ncol(data)), defaultMethod = c("pmm",
"logreg", "polyreg", "polr"), maxit = 5, diagnostics = TRUE,
printFlag = TRUE, seed = NA, imputationMethod = NULL,
defaultImputationMethod = NULL, data.init = NULL, ...)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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