Perform an adonis test

This function executes the adonis2 function of the vegan package and returns the result.

Usage

perform_adonis(ta, predictors, permutations = 999, ...)

Arguments

ta

A tidytacos object.

predictors

A character vector with predictors to include in the model.

permutations

The number of permutations (more permutations takes longer but gives a more accurate p-value).

...

Arguments passed on to vegan::adonis2

formula

Model formula. The left-hand side (LHS) of the formula must be either a community data matrix or a dissimilarity matrix, e.g., from vegdist or dist. If the LHS is a data matrix, function vegdist will be used to find the dissimilarities. The right-hand side (RHS) of the formula defines the independent variables. These can be continuous variables or factors, they can be transformed within the formula, and they can have interactions as in a typical formula.

data

the data frame for the independent variables, with rows in the same order as the community data matrix or dissimilarity matrix named on the LHS of formula.

method

the name of any method used in vegdist to calculate pairwise distances if the left hand side of the formula was a data frame or a matrix.

sqrt.dist

Take square root of dissimilarities. This often euclidifies dissimilarities.

add

Add a constant to the non-diagonal dissimilarities such that all eigenvalues are non-negative in the underlying Principal Co-ordinates Analysis (see wcmdscale for details). Choice "lingoes" (or TRUE) use the recommended method of Legendre & Anderson (1999: “method 1”) and "cailliez" uses their “method 2”.

by

by = NULL will assess the overall significance of all terms together, by = "terms" will assess significance for each term (sequentially from first to last), setting by = "margin" will assess the marginal effects of the terms (each marginal term analysed in a model with all other variables), by = "onedf" will analyse one-degree-of-freedom contrasts sequentially. The argument is passed on to anova.cca.

parallel

Number of parallel processes or a predefined socket cluster. With parallel = 1 uses ordinary, non-parallel processing. The parallel processing is done with parallel package.

na.action

Handling of missing values on the right-hand-side of the formula (see na.fail for explanation and alternatives). Missing values are not allowed on the left-hand-side. NB, argument subset is not implemented.

strata

Groups within which to constrain permutations. The traditional non-movable strata are set as Blocks in the permute package, but some more flexible alternatives may be more appropriate.

Value

An object of class "adonis" (see adonis).

Details

Samples where one or more predictors are NA are removed.

Examples

res <- urt %>%
  perform_adonis(c("plate", "method"), by = "terms")
res
#> Permutation test for adonis under reduced model
#> Terms added sequentially (first to last)
#> Permutation: free
#> Number of permutations: 999
#> 
#> adonis2(formula = as.formula(paste("counts_matrix", formula_RHS, sep = " ~ ")), data = metadata, permutations = permutations, by = "terms")
#>           Df SumOfSqs      R2      F Pr(>F)  
#> plate      1    0.663 0.00905 1.9454  0.018 *
#> method     1    0.677 0.00924 1.9863  0.014 *
#> Residual 211   71.913 0.98171                
#> Total    213   73.253 1.00000                
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1