MultiDimen_test {CNPS} | R Documentation |

## Multivariate Permutation Test and Paired Comparisons

### Description

Performs multivariate permutation tests, including paired tests.

### Usage

```
MultiDimen_test (data , stat = "HT",pair=FALSE, method_p = "sampling",rank = FALSE,
diff = FALSE , samplenum = 1000)
```

### Arguments

`data` |
a matrix or data frame of data values. |

`stat` |
a character string specifying the statistic, must be one of "HT" (default), "tmax", "tmaxabs", "wsum", "zmax", "zmaxabs". |

`pair` |
a logical indicating whether you want a paired test. |

`method_p` |
a character string specifying the method of calculating p-value, must be one of "sampling" (default), " asymptotic", "exact". |

`rank` |
a logical indicating whether you want Wilcoxon test. |

`diff` |
a logical indicating whether you want to present which variables are different. |

`samplenum` |
a number specifying the number of sampling. |

### Details

The test can be used for multivariate permutation test and multivariate paired comparisons.

When doing multivariate paired comparisons, that is `pair = TRUE`

, the statistic `wsum`

is not suitable. Meanwhile, asymptotic method can only be used when statistic is `HT`

. Besides, the second last column of the data must only contain two unique numbers to represent the two samples; the last column represents different pairs.

When doing multivariate permutation test, that is `pair = FALSE`

, the statistic `zmax`

and `zmaxabs`

are not suitable. Meanwhile, the last column of the data must only contain 0 and 1 to represent the two samples. Besides, asymptotic method can not be used when statistic is `tmax`

or `tmaxabs`

.

### Value

`method` |
the test which is used. |

`score` |
a character string describing the score used for test. |

`stat` |
the test statistic. |

`pval` |
p-value for the test. |

`alternative` |
a character string describing the alternative hypothesis. |

`addition` |
a character string describing which variable is different in two samples.(presents only if pair = FALSE) |

### Author(s)

Jiasheng Zhang, Feng Yu, Yangyang Zhang, Siwei Deng. Tutored by YuKun Liu and Dongdong Xiang.

### References

Higgins, J. J. (2004). An introduction to modern nonparametric statistics. Pacific Grove, CA: Brooks/Cole.

### Examples

```
## Multivariate permutation test
data = matrix(c(6.81, 6.16, 5.92, 5.86, 5.80, 5.39,
6.68, 6.30, 6.12, 5.71, 6.09, 5.28,
6.34, 6.22, 5.90, 5.38, 5.20, 5.46,
6.68, 5.24, 5.83, 5.49, 5.37, 5.43,
6.79, 6.28, 6.23, 5.85, 5.56, 5.38,
6.85, 6.51, 5.95, 6.06, 6.31, 5.39,
6.64, 5.91, 5.59, 5.41, 5.24, 5.23,
6.57, 5.89, 5.32, 5.41, 5.32, 5.30,
6.84, 6.01, 5.34, 5.31, 5.38, 5.45,
6.71, 5.60, 5.29, 5.37, 5.26, 5.41,
6.58, 5.63, 5.38, 5.44, 5.17, 6.62,
6.68, 6.04, 5.62, 5.31, 5.41, 5.44),
nrow = 12,ncol = 6,byrow = TRUE
)
data=as.matrix(data)
index=c(rep(0,6),rep(1,6))
data = cbind(data,index)
x = MultiDimen_test(data , rank = FALSE , method_p = "sampling", samplenum = 100
, stat = "HT",diff = TRUE )
y = MultiDimen_test(data , rank = FALSE , method_p = "sampling", samplenum = 100
, stat = "tmax",diff = TRUE)
z = MultiDimen_test(data , rank = TRUE , method_p = "sampling" , stat = "HT"
, samplenum = 100,diff = TRUE)
## Multivaraite paired comparisons
data = matrix(c(82, 60, 72, 62,
75, 71, 70, 68,
85, 59, 87, 64,
90, 77, 87, 78),
nrow = 4,ncol = 4,byrow = TRUE
)
x = data[,c(1,2)]
y = data[,c(3,4)]
data = cbind(rbind(x,y) , c(0,0,1,1) , c(1,2,1,2))
MultiDimen_test(data , method_p = "exact" , pair = TRUE)
```

*CNPS*version 1.0.0 Index]