rda_per_time: Redundancy Analysis (RDA) per factor level
In EDiLD/qetx: Quantitative Ecotoxicology with R

Description Usage Arguments Value Author(s) See Also Examples

This function runs a RDA on each timepoint. Signuificance of contraining terms is assessed via permutaions. This is mainly a wrapper around rda and anova.cca.

rda_per_time(response, treatment, time, nperm = NULL)

## S3 method for class 'rdas'
print(x, ...)

`response`	Multivariate response data.
`treatment`	A variable for treatments.
`time`	A factor defining the observation times
`...`	other arguments passed to `anova.cca`
`x`	an rdas-object.

A list of class rdas. One list entry for every time point. Each list entry holds the resulting rda-model ($rda) or the result of a permutation test ($anova).

Eduard Szoecs szoe8822@uni-landau.de

prc anova.cca rda

# Chlorpyrifos experiment and experimental design
data(pyrifos, package = 'vegan')
week <- gl(11, 12, labels=c(-4, -1, 0.1, 1, 2, 4, 8, 12, 15, 19, 24))
dose <- factor(rep(c(0.1, 0, 0, 0.9, 0, 44, 6, 0.1, 44, 0.9, 0, 6), 11))
# PRC
mod <- prc(pyrifos, dose, week)
# RDA per week, using ln-transformed dose as continuous explaing variable
mod_pw <- rda_per_time(pyrifos, log(10*as.numeric(as.character(dose)) + 1), week)
# extract p-values for each week
sapply(mod_pw, function(x) x$anova[1, 5])