# LittleMCAR: Little's missing completely at random (MCAR) test In BaylorEdPsych: R Package for Baylor University Educational Psychology Quantitative Courses

## Description

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

## Usage

 `1` ```LittleMCAR(x) ```

## 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.

md.pattern

## Examples

 ```1 2``` ```data(EndersTable1_1) LittleMCAR(EndersTable1_1) ```

### 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.