R: t-test for Clustered Data

t.test.cluster {Hmisc} | R Documentation

## t-test for Clustered Data

### Description

Does a 2-sample t-test for clustered data.

### Usage

    t.test.cluster(y, cluster, group, conf.int = 0.95)
    ## S3 method for class 't.test.cluster'
    print(x, digits, ...)

### Arguments

`y` | normally distributed response variable to test
`cluster` | cluster identifiers, e.g. subject ID
`group` | grouping variable with two values
`conf.int` | confidence coefficient to use for confidence limits
`x` | an object created by `t.test.cluster`
`digits` | number of significant digits to print
`...` | unused

### Value

a matrix of statistics of class `t.test.cluster`

### Author(s)

Frank Harrell

### References

Donner A, Birkett N, Buck C, Am J Epi 114:906-914, 1981.

Donner A, Klar N, J Clin Epi 49:435-439, 1996.

Hsieh FY, Stat in Med 8:1195-1201, 1988.

### See Also

`t.test`

### Examples

    set.seed(1)
    y <- rnorm(800)
    group <- sample(1:2, 800, TRUE)
    cluster <- sample(1:40, 800, TRUE)
    table(cluster,group)
    t.test(y ~ group)   # R only
    t.test.cluster(y, cluster, group)
    # Note: negate estimates of differences from t.test to
    # compare with t.test.cluster

[Package Hmisc version 4.2-0 Index]