| mice.mids {mice} | R Documentation |
Takes a mids object, and produces a new object of class mids.
## S3 method for class 'mids': mice(obj, maxit=1, diagnostics=TRUE, printFlag=TRUE)
obj |
An object of class mids, typically produces by a previous call
to mice() or mice.mids() |
maxit |
The number of additional Gibbs sampling iterations. |
diagnostics |
A Boolean flag. If TRUE, diagnostic information will be appended to
the value of the function. If FALSE, only the imputed data are saved.
The default is TRUE. |
printFlag |
A Boolean flag. If TRUE, diagnostic information during the Gibbs sampling
iterations will be written to the command window. The default is TRUE. |
This function enables the user to split up the computations of the Gibbs sampler into smaller parts. This is useful for the following reasons:
Note: The imputation model itself is specified in the mice() function
and cannot be changed with mice.mids.
The state of the random generator is saved with the mids object.
Stef van Buuren, Karin Groothuis-Oudshoorn, 2000
Van Buuren, S., Groothuis-Oudshoorn, K. (2009) MICE: Multivariate Imputation by Chained Equations in R. Journal of Statistical Software, forthcoming. http://www.stefvanbuuren.nl/publications/MICE in R - Draft.pdf
imp1 <- mice(nhanes,maxit=1) imp2 <- mice.mids(imp1) # yields the same result as imp <- mice(nhanes,maxit=2) # for example: # # > imp$imp$bmi[1,] # 1 2 3 4 5 # 1 30.1 35.3 33.2 35.3 27.5 # > imp2$imp$bmi[1,] # 1 2 3 4 5 # 1 30.1 35.3 33.2 35.3 27.5 #