nst.panova | R Documentation |

Permutational multivariate ANOVA test for stochasticity ratio and normalized stochasticity ratio between treatments

nst.panova(nst.result, group=NULL, rand=999, trace=TRUE, SES=FALSE, RC=FALSE)

`nst.result` |
list object, the output of nsto, must have "details" |

`group` |
nx1 matrix, if the grouping is different from the nst.result. default is NULL, means to use the grouping in nst.result. |

`rand` |
integer, randomization times for permuational test |

`trace` |
logic, whether to show message when randomizing. |

`SES` |
Logic, whether to perform the test for standardized effect size (SES). SES is (observed dissimilarity - mean of null dissimilarity)/standard deviation of null dissimilarity. default is FALSE. |

`RC` |
Logic, whether to perform the test for modified Raup-Crick metric (RC). RC is percentage of null dissimilarity lower than observed dissimilarity x 2 - 1. default is FALSE. |

PERMANOVA for stochasticity ratio (ST or NST or MST) or SES or RC is based on the comparison of F values between observed pattern and the permutated patterns where samples are randomly shuffled regardless of treatments. However, it is a bit different from PERMANOVA for dissimilarity. The PERMANOVA of stochasticity ratio here is to ask whether the ST values within a group is higher than those within another group. But the PERMANOVA of dissimilarity is to ask whether the between-group dissimilarity is higher than within-group dissimilarity.

Output is a data.frame object.

`index` |
name of index |

`group1` |
treatment/group name |

`group2` |
treatment/group name |

`Index.group1` |
index value in group1 |

`Index.group2` |
index value in group2 |

`Difference` |
index.group1 - index.group2 |

`F.obs` |
F value |

`P.anova` |
P value of parametric ANOVA test |

`P.panova` |
P value of permutational ANOVA test |

`P.perm` |
P value of permutational test of the difference |

Version 7: 2021.10.29, add PERMANOVA test for SES and RC. Version 6: 2021.9.28, avoid error for special cases in permutation. Version 5: 2021.8.25, revised to avoid error for special cases in MST calculation. Version 4: 2020.10.14, debug some error when replecate number is low and edit details in help. Version 3: 2019.10.8, Update reference. Version 2: 2019.5.10 Version 1: 2017.12.30

Daliang Ning

Ning D., Deng Y., Tiedje J.M. & Zhou J. (2019) A general framework for quantitatively assessing ecological stochasticity. Proceedings of the National Academy of Sciences 116, 16892-16898. doi:10.1073/pnas.1904623116.

`tNST`

, `nst.boot`

data(tda) comm=tda$comm group=tda$group tnst=tNST(comm=comm, group=group, rand=20, output.rand=TRUE, nworker=1) # rand is usually set as 1000, here set rand=20 to save test time. nst.pova=nst.panova(nst.result=tnst, rand=99) # rand is usually set as 999, here set rand=99 to save test time.

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