NesAnovaNested multivariate analysis made easy. | |
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NesAnova Ranking & Summary
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- License:
- Freeware
- Publisher Name:
- Pierre Legendre
- Operating Systems:
- Windows All
- File Size:
- 142 KB
NesAnova Tags
- analyzer analysis Analyze multivariate Nested parentheses multivariate analysis nested quote nested object viewer nested object view multivariate dataset nested clade analysis Nested Clade nested multivariate analysis canonical redundancy analysis compute simple manova multivariate estimation multivariate space find Nested Tandem Repeats multivariate nonlinear data multivariate analytical softwar multivariate data analysis multivariate regression multivariate curve resolution nested nested rectangles
NesAnova Description
NesAnova is a small, command prompt based application specially designed to carry out nested multivariate analysis of variance by canonical redundancy analysis, with permutation testing, using 2 or 3 factors ( for example, one main factor plus 1 or 2 nested factors). If a single factor is present, the program computes simple manova with permutation test. The response table subjected to the analysis can be a single variable or a multivariate data table. The primary interest of this program is to allow nested analysis of variance to be carried out for community composition data (species presence-absence or abundance data tables). Three choices are open with such data: · If there are very few zeros in the species response data table, the abundances can be analysed directly without further transformation. This is a rare situation since community composition data are usually obtained across a gradient of some sort, natural or experimental, which aims at maximizing the observed variability, so that many species that have unimodal distributions along the gradient(s) (i.e., those that have an abundance optimum) are represented in the table by many zeros. · In most cases, the community composition data (species presence-absence or abundance) are transformed in some way. This can be done using one of the transformations proposed by Legendre & Gallagher (2001); these transformations are available in the program. · An alternative method is to compute a matrix of ecological distances (D) among sites. For species presence-absence data, the one-complements of the indices of Jaccard or Sørensen are often used. For species abundance data, ecologists often rely upon the Steinhaus/Odum/Bray-Curtis distance function. Principal coordinate analysis of that D matrix produces a new rectangular data table that can be used as input for nested manova (Legendre & Anderson 1999).
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