LittleMCAR: Little's missing completely at random (MCAR) test

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/LittleMCAR.R

Description

Uses Little's test to assess for missing completely at random for multivariate data with missing values

Usage

1

Arguments

x

A data frame or data matrix of no more than 50 variables

Details

Depending on the sample size and number of missing data patterns, this function could take a long time to run.

Value

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

Author(s)

A. Alexander Beaujean

References

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.

See Also

md.pattern

Examples

1
2

Example output

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

BaylorEdPsych documentation built on May 1, 2019, 8:21 p.m.