Description Usage Arguments Details Value Author(s) References See Also Examples
Uses Little's test to assess for missing completely at random for multivariate data with missing values
1 | LittleMCAR(x)
|
x |
A data frame or data matrix of no more than 50 variables |
Depending on the sample size and number of missing data patterns, this function could take a long time to run.
chi.square |
Chi-square value |
df |
Degrees of freedom used for chi-square |
missing.patterns |
Number of missing data patterns |
amount.missing |
Amount and percent of mssing data |
data |
The data, organized my missing data patterns |
A. Alexander Beaujean
Little, R. J. A. (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83(404), 1198–1202.
md.pattern
1 2 |
Loading required package: mvnmle
this could take a while$chi.square
[1] 14.63166
$df
[1] 5
$p.value
[1] 0.01205778
$missing.patterns
[1] 4
$amount.missing
IQ JP WB
Number Missing 0 10.0 3.00
Percent Missing 0 0.5 0.15
$data
$data$DataSet1
IQ JP WB
11 99 7 6
12 105 10 12
13 105 11 14
14 106 15 10
16 112 10 10
17 113 12 14
18 115 14 14
19 118 16 12
20 134 12 11
$data$DataSet2
IQ JP WB
1 78 NA 13
2 84 NA 9
3 84 NA 10
4 85 NA 10
6 91 NA 3
7 92 NA 12
8 94 NA 3
9 94 NA 13
$data$DataSet3
IQ JP WB
15 108 10 NA
$data$DataSet4
IQ JP WB
5 87 NA NA
10 96 NA NA
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