R: Preliminary Manipulations on Matrix of Incomplete Mixed Data
prelim.mix
R Documentation
Preliminary Manipulations on Matrix of Incomplete Mixed Data
Description
This function performs grouping and sorting operations on a mixed
dataset with missing values. It creates a list that is
needed for input to em.mix, da.mix,
imp.mix, etc.
Usage
prelim.mix(x, p)
Arguments
x
data matrix containing missing values. The rows of x correspond to
observational units, and the columns to variables. Missing values are
denoted by NA. The categorical variables must be in
the first p columns
of x, and they must be coded with consecutive positive integers
starting with 1. For example, a binary variable must be coded as 1,2
rather than 0,1.
p
number of categorical variables in x
Value
a list of twenty-nine (!) components that summarize various features
of x after the data have been collapsed, centered, scaled, and sorted
by missingness patterns. Components that might be of interest to the
user include:
nmis
a vector of length ncol(x) containing the number of
missing values for each variable in x.
r
matrix of response indicators showing the missing data patterns in
x.
Observed values are indicated by 1 and missing values by 0. The row
names give the number of observations in each pattern, and the columns
correspond to the columns of x.
References
Schafer, J. L. (1996) Analysis of Incomplete Multivariate Data.
Chapman & Hall, Chapter 9.