MCPAN-package {MCPAN} | R Documentation |
Multiple contrast tests and simultaneous confidence intervals using normal approximation, if individuals are randomly assigned to treatments in a oneway layout. If the variable of interest is dichotomous, the binom-methods can be used. If the variable of interest is the rate of tumours in long-term rodent carcinogenicity trials (without cause of death information), the poly3-methods can be used. The methods implemented in this package are NOT published in peer-reviewed journals so far.
Package: | MCPAN |
Type: | Package |
Version: | 1.0-4 |
Date: | 2007-08-15 |
License: | GPL |
Frank Schaarschmidt, Daniel Gerhard Maintainer: Frank Schaarschmidt <schaarschmidt@biostat.uni-hannover.de>
For long-term rodent carcinogenicity data: The assumptions of poly-3-adjustment are outlined in:
Bailer, J.A. and Portier, C.J. (1988): Effects of treatment-induced mortality and tumor-induced mortality on tests for carcinogenicity in small samples. Biometrics 44, 417-431.
Peddada, S.D., Dinse, G.E., and Haseman, J.K. (2005): A survival-adjusted quantal response test for comparing tumor incidence rates. Applied Statistics 54, 51-61.
For correlation of multiple contrasts of binomial proportions, see: Bretz F, Hothorn L.: Detecting dose-response using contrasts: asymptotic power and sample size determination for binomial data. Statistics in Medicine 2002; 21: 3325-3335.
Simulation results (coverage probability of simultaneous confidence intervals) for the binomial proportions and poly-3-adjusted tumour rates can be found in:
Sill, M. (2007): .... Master thesis, Institute of Biostatistics, Leibniz University Hannover.
# # # 1) # Adjusted p-values and simultaneous confidence intervals # for 2xk tables of binomial data: # binomtest, binomci # Difference of proportions binomRDtest(x=c(2,6,4,13), n=c(34,33,36,34), names=c("Placebo", "50", "75", "150"), type="Dunnett", method="ADD1") binomRDci(x=c(2,6,4,13), n=c(34,33,36,34), names=c("Placebo", "50", "75", "150"), type="Dunnett", method="ADD1") # Odds ratios: binomORci(x=c(2,6,4,13), n=c(34,33,36,34), names=c("Placebo", "50", "75", "150"), type="Dunnett") # For more details on evaluation, # see: # ?liarozole data(liarozole) # # # 2) # Adjusted p-values and simultaneous confidence intervals # for poly-3-adjusted tumour rates: # poly3test, poly3ci data(methyl) methyl # poly-3-adjusted sample estimates: poly3estf(time=methyl$death, status=methyl$tumour, f=methyl$group) # Simultaneous Add-1-confidence intervals # for difference to the control group: poly3ci(time=methyl$death, status=methyl$tumour, f=methyl$group, method="ADD1", type="Dunnett", alternative="greater") # Test for trend, based on Changepoint contrasts: poly3test(time=methyl$death, status=methyl$tumour, f=methyl$group, method="ADD1", type="Changepoint", alternative="greater") # # # 3) Plot of confidence intervals # created by binomci and poly3ci: MethylCI <- poly3ci(time=methyl$death, status=methyl$tumour, f=methyl$group, method="ADD1", type="Dunnett", alternative="greater") plot(MethylCI)