prelim.norm: Preliminary manipulations for a matrix of incomplete
continuous data.
Description
Sorts rows of x by missingness patterns, and centers/scales
columns of x. Calculates various bookkeeping quantities needed
for input to other functions, such as em.norm and da.norm.
Usage
prelim.norm(x)
Value
a list of thirteen components that summarize various features of x
after the data have been 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. This vector has names that correspond
to the column names of x, if any.
r
matrix of response indicators showing the missing data patterns
in x. Dimension is (S,p) where S is the number of distinct
missingness patterns in the rows of x, and p is the number of
columns 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 column names correspond to the column names of
x.
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.