mids {mice} | R Documentation |
An object containing a multiply imputed data set. The
mids
object is generated by the mice
and mice.mids
functions. The
mids
class of objects has methods for the following generic
functions: print
, summary
, plot
.
is.mids(x) ## S4 method for signature 'mids' print(x,...) ## S4 method for signature 'mids' summary(object,...) ## S4 method for signature 'mids,ANY' plot(x, y, ...) plot.mids(x, y=NULL, theme=mice.theme(), layout=c(2,3), type="l", col=1:10, lty=1, ...)
x, object |
A object of class |
y |
A character vector containing variable names, an integer vector of indices of imputed variables, a logical vector of
|
theme |
List of settings with selected graphical parameters to control the lattice function |
layout |
Vector of two numbers controlling the number of panels in horizontal and vertical direction, respectively. |
type |
Plot type parameter. |
col |
Color parameter. |
lty |
Line type parameter. |
... |
Currently not used. |
call |
The call that created the object. |
data |
A copy of the incomplete data set. |
m |
The number of imputations. |
nmis |
An array containing the number of missing observations per column. |
imp |
A list of nvar components with the generated multiple imputations.
Each part of the list is a |
method |
A vector of strings of length(nvar) specifying the elementary imputation method per column. |
predictorMatrix |
A square matrix of size |
visitSequence |
The sequence in which columns are visited. |
post |
A vector of strings of length |
seed |
The seed value of the solution. |
iteration |
Last Gibbs sampling iteration number. |
lastSeedValue |
The most recent seed value. |
chainMean |
A list of |
chainVar |
A list with similar structure of |
pad |
A list containing various settings of the padded imputation model, i.e. the imputation model after creating dummy variables. Normally, this array is only useful for error checking. |
Stef van Buuren, Karin Groothuis-Oudshoorn, 2000
van Buuren S and Groothuis-Oudshoorn K (2011).
mice
: Multivariate Imputation by Chained Equations in R
.
Journal of Statistical Software, 45(3), 1-67.
http://www.jstatsoft.org/v45/i03/