ANOSIM

ANOSIM is a rank-based permutation test that compares the mean rank of between-group dissimilarities with the mean rank of within-group dissimilarities through the statistic R.

ANOSIM은 집단 간 비유사도의 평균 순위와 집단 내 비유사도의 평균 순위를 통계량 R로 비교하는 순위 기반 순열 검정입니다.

Are samples within the same group more similar to each other than to samples from other groups?

같은 집단의 표본끼리가 다른 집단의 표본보다 더 비슷한지 어떻게 검정하나요?

ANOSIM ranks all pairwise dissimilarities and computes R from the difference between mean between-group and within-group ranks, so R near 1 means groups are well separated and R near 0 means no separation. Significance comes from permuting group labels, and pairwise R values show which groups differ.

When to use ANOSIM

• Testing whether predefined groups of samples differ in multivariate composition
• Only the rank order of dissimilarities is considered reliable
• A simple separation statistic between -1 and 1 is wanted

When to use something else

• You need the share of variation explained or multi-factor designs: use PERMANOVA
• You want to compare group spread rather than location: use PERMDISP

Assumptions and requirements

• Observations are exchangeable under the null hypothesis
• Similar dispersion among groups, since ANOSIM is also sensitive to spread

What the analysis reports

• Global R with mean between-group and within-group ranks
• Permutation p-value
• Pairwise R with Benjamini-Hochberg adjusted p-values
• A parametric dispersion check

How to report it

An analysis of similarities on Bray-Curtis dissimilarities (N = [n], [k] groups, [value] permutations) gave a global R = [value], p = [value].

Related methods

• PERMANOVA
• Multivariate Dispersion Test (PERMDISP)
• SIMPER Dissimilarity Contributions

Run ANOSIM on Quorant