Performs a permutation test of differences in means between groups of censored data.

cenpermanova(y1, y2, grp, R = 9999, printstat = TRUE)

## Arguments

y1 The column of data values plus detection limits. The column of indicators, where 1 (or TRUE) indicates a detection limit in the y1 column, and 0 (or FALSE) indicates a detected value in y1. Grouping or factor variable. Can be either a text or numeric value indicating the group assignment. The number of permutations used. Default is 9999. Logical TRUE/FALSE option of whether to print the resulting statistics in the console window, or not. Default is TRUE.

## Value

Permutation test results with the number of permutations, range in test statistics and p-value values through the various permutations. Group means are also listed.

## Details

Because this is a permutation test it avoids the problem with MLE tests (see cenanova) that assume a normal distribution. No values are modeled as below zero and group means and p-values are trustworthy.

## References

Good, P., 2000. Permutation Tests: A Practical Guide to Resampling Methods for Testing Hypotheses, 2nd ed, Springer Series in Statistics. Springer-Verlag, New York, NY. doi: 10.1007/978-1-4757-3235-1

Helsel, D.R., 2011. Statistics for Censored Environmental Data using Minitab and R, 2nd ed. John Wiley & Sons, USA, N.J.

## Examples


data(PbHeron)
cenpermanova(PbHeron$Liver,PbHeron$LiverCen,PbHeron$DosageGroup) #> Permutation test of mean CensData: PbHeron$Liver   by Factor: PbHeron\$DosageGroup
#>      9999 Permutations
#> Test Statistic = 1122 to 1122       p = 0.0015 to 0.002
#>
#> mean(High)    mean(Low)
#>     9.2880       0.1204