cen1way {NADA2} | R Documentation |
Peto-Peto one-factor test
Description
Performs a Peto-Peto nonparametric test of differences in cdfs between groups. If more than two groups, the test is followed by a nonparametric multiple comparison test. Uses the BH method of adjusting p-values.
Usage
cen1way(x1, x2, group, mcomp.method = "BH", printstat = TRUE)
Arguments
x1 |
The column of data values plus detection limits |
x2 |
The column of indicators, where 1 (or |
group |
Grouping or factor variable. Can be either a text or numeric value indicating the group assignment. |
mcomp.method |
One of the standard methods for adjusting p-values for multiple comparisons. Type ?p.adjust for the list of possible methods. Default is Benjamini-Hochberg "BH" false discover rate. |
printstat |
Logical |
Value
A list of summary statistics for each group evaluated containing the following components:
-
N
Number of samples -
PctND
Percentage of non-detects -
KMmean
Kaplan-Meier estimate of the mean -
KMsd
Kaplan-Meier estimate of standard deviation -
KMmedian
Kaplan-Meier estmate of the median
Peto-Peto test results including Chi-Squared value, degrees of freedom and p-value
of the test.
If more than two groups, p-values
of the pairwise multiple comparisons, adjusted using the BH false-discovery rate, are reported.
References
Helsel, D.R., 2011. Statistics for Censored Environmental Data using Minitab and R, 2nd ed. John Wiley & Sons, USA, N.J.
Peto, R., Peto, J., 1972. Asymptotically Efficient Rank Invariant Test Procedures. Journal of the Royal Statistical Society. Series A (General) 135, 185. doi: 10.2307/2344317
Benjamini, Y., Hochberg, Y., 1995. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society. Series B (Methodological), 57, 289-300.
Examples
data(PbHeron)
# Two Groups
cen1way(PbHeron$Liver,PbHeron$LiverCen,PbHeron$DosageGroup)
# More than two groups
cen1way(PbHeron$Liver,PbHeron$LiverCen,PbHeron$Group)