ecodist (version 1.2.7)

permresults: Mantel test results for number of permutations, correlation and dataset size.

Description

These results explore the variability in randomization tests of significance and in bootstrap confidence limits for different sample sizes, strengths of relationship and numbers of permutations.

Usage

data(permresults)

Details

These simulation results are included here because the entire simulation takes an extremely long time to run. The tests explored how the p-value and confidence limits varied with: - number of samples (10 (45 dissimilarities), 25 (300), 50 (1225), 100 (4950)) - number of permutations: 500, 1000, 10000, 100000, 1000000 - number of bootstrap samples: 100, 500, 1000, 10000, 100000 - correlation of the original data: 0.01, 0.05, 0.10, 0.25, 0.50 The larger correlation values were omitted for the larger sample sizes because they were always highly signficant, and an additional low value of 0.025 was added for the largest sample size.

The method used to generate the data is shown in the example section.

Examples

data(permresults)

# Simulation Method
# example for sample size 10, correlation of 0.01

permresults <- data.frame(matrix(0, nrow=1000, ncol=17))
colnames(permresults) <- c("n", "r", "p500", "l100", "u100", "p1000", "l500", "u500", "p10000", "l1000", "u1000", "p100000", "l10000", "u10000", "p1000000", "l100000", "u100000")

# generate correlated data
corxy.len010.r010 <- corgen(len= 10, r= 0.01, epsilon=0.0001)

all.nperm <- c(500, 1000, 10000, 100000, 1000000)
all.nboot <- c(100, 500, 1000, 10000, 100000)

for(i in 1:1000) {
    permresults[i, 1] <- 10
    permresults[i, 2] <- 0.01
    for(j in 1:5) {
# record p-value, lower and upper confidence limits
        thismantel <- mantel(corxy.len010.r010$y ~ corxy.len010.r010$x, nperm=all.nperm[j], nboot=all.nboot[j])
        permresults[i, (3*j):(3*j + 2)] <- c(thismantel[c(2,5,6)])
    }
}