RS.trend.test {CorrBin} | R Documentation |

## Rao-Scott trend test

### Description

`RS.trend.test`

implements the Rao-Scott adjusted Cochran-Armitage test
for linear increasing trend with correlated data.

### Usage

```
RS.trend.test(cbdata)
```

### Arguments

`cbdata` |
a |

### Details

The test is based on calculating a design effect for each cluster by dividing the observed variability by the one expected under independence. The number of responses and the cluster size are then divided by the design effect, and a Cochran-Armitage type test statistic is computed based on these adjusted values.

The implementation aims for testing for *increasing* trend, and a
one-sided p-value is reported. The test statistic is asymptotically normally
distributed, and a two-sided p-value can be easily computed if needed.

### Value

A list with components

`statistic` |
numeric, the value of the test statistic |

`p.val` |
numeric, asymptotic one-sided p-value of the test |

### Author(s)

Aniko Szabo, aszabo@mcw.edu

### References

Rao, J. N. K. & Scott, A. J. A (1992) Simple Method for the
Analysis of Clustered Data *Biometrics*, 48, 577-586.

### See Also

`SO.trend.test`

, `GEE.trend.test`

for
alternative tests; `CBData`

for constructing a CBData object.

### Examples

```
data(shelltox)
RS.trend.test(shelltox)
```

*CorrBin*version 1.6.1 Index]