Description Usage Arguments Value References See Also Examples
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.
1  prelim.mix(x, p)

x 
data matrix containing missing values. The rows of x correspond to
observational units, and the columns to variables. Missing values are
denoted by 
p 
number of categorical variables in x 
a list of twentynine (!) 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 
r 
matrix of response indicators showing the missing data patterns in

Schafer, J. L. (1996) Analysis of Incomplete Multivariate Data. Chapman \& Hall, Chapter 9.
em.mix
, ecm.mix
,
da.mix
, dabipf.mix
, imp.mix
,
getparam.mix
1 2 3 4  data(stlouis)
s < prelim.mix(stlouis, 3) # do preliminary manipulations
s$nmis # look at nmis
s$r # look at missing data patterns

G D1 D2 R1 V1 R2 V2
0 28 28 21 30 16 17
G D1 D2 R1 V1 R2 V2
12 1 1 1 1 1 1 1
1 1 0 1 1 1 1 1
8 1 1 0 1 1 1 1
6 1 0 0 1 1 1 1
1 1 1 1 0 1 1 1
1 1 0 1 0 1 1 1
1 1 1 0 0 1 1 1
3 1 0 0 0 1 1 1
3 1 1 1 1 0 1 1
1 1 0 0 1 0 1 1
1 1 1 1 0 0 1 1
6 1 0 1 0 0 1 1
2 1 0 0 0 0 1 1
4 1 1 1 1 1 0 1
1 1 0 1 1 0 0 1
1 1 0 0 0 0 0 1
3 1 1 1 1 0 1 0
1 1 1 1 0 0 1 0
2 1 0 1 0 0 1 0
1 1 0 0 0 0 1 0
1 1 1 0 1 1 0 0
1 1 0 0 1 1 0 0
4 1 1 1 1 0 0 0
2 1 1 0 1 0 0 0
1 1 0 0 1 0 0 0
1 1 0 1 0 0 0 0
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