DAU.test {agricolae} | R Documentation |

## Finding the Variance Analysis of the Augmented block Design

### Description

Analysis of variance Augmented block and comparison mean adjusted.

### Usage

```
DAU.test(block, trt, y, method = c("lsd","tukey"),alpha=0.05,group=TRUE,console=FALSE)
```

### Arguments

`block` |
blocks |

`trt` |
Treatment |

`y` |
Response |

`method` |
Comparison treatments |

`alpha` |
Significant test |

`group` |
TRUE or FALSE |

`console` |
logical, print output |

### Details

Method of comparison treatment. lsd: Least significant difference. tukey: Honestly significant differente. The controls can have different repetitions, at least two, do not use missing data.

### Value

`means` |
Statistical summary of the study variable |

`parameters` |
Design parameters |

`statistics` |
Statistics of the model |

`comparison` |
Comparison between treatments |

`groups` |
Formation of treatment groups |

`SE.difference` |
Standard error of: |

`vartau` |
Variance-covariance matrix of the difference in treatments |

### Author(s)

F. de Mendiburu

### References

Federer, W. T. (1956). Augmented (or hoonuiaku) designs. Hawaiian Planters, Record LV(2):191-208.

### See Also

`BIB.test`

, `duncan.test`

, `durbin.test`

,
`friedman`

, `HSD.test`

, `kruskal`

,
`LSD.test`

, `Median.test`

, `PBIB.test`

,
`REGW.test`

, `scheffe.test`

, `SNK.test`

,
`waerden.test`

, `waller.test`

, `plot.group`

### Examples

```
library(agricolae)
block<-c(rep("I",7),rep("II",6),rep("III",7))
trt<-c("A","B","C","D","g","k","l","A","B","C","D","e","i","A","B","C","D","f","h","j")
yield<-c(83,77,78,78,70,75,74,79,81,81,91,79,78,92,79,87,81,89,96,82)
out<- DAU.test(block,trt,yield,method="lsd", group=TRUE)
print(out$groups)
plot(out)
```

*agricolae*version 1.3-7 Index]