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pairwiseCImethodsCont {pairwiseCI}

Confidence intervals for two sample comparisons of continuous data
Package: 
pairwiseCI
Version: 
0.1-21

Description

Confidence interval methods available for pairwiseCI for comparison of two independent samples. Methods for continuous variables.

Usage

Param.diff(x, y, conf.level=0.95, alternative="two.sided", ...)
Param.ratio(x, y, conf.level=0.95, alternative="two.sided", ...)

Lognorm.diff(x, y, conf.level=0.95, alternative="two.sided", sim=10000, ...)
Lognorm.ratio(x, y, conf.level=0.95, alternative="two.sided", sim=10000, ...)

HL.diff(x, y, conf.level=0.95, alternative="two.sided", ...)
HL.ratio(x, y, conf.level=0.95, alternative="two.sided", ...)

Median.diff(x, y, conf.level=0.95, alternative="two.sided", ...)
Median.ratio(x, y, conf.level=0.95, alternative="two.sided", ...)

Arguments

x
vector of observations in the first sample
y
vector of observations in the second sample
alternative
character string, either "two.sided", "less" or "greater"
conf.level
the comparisonwise confidence level of the intervals, where 0.95 is default
sim
a single integer value, specifying the number of samples to be drawn for calculation of the empirical distribution of the generalized pivotal quantities
...
further arguments to be passed to the individual methods, see details

Details

  • Param.diff calculates the confidence interval for the difference in means of two Gaussian samples by calling t.test in package stats, assuming homogeneous variances if var.equal=TRUE, and heterogeneous variances if var.equal=FALSE (default);
  • Param.ratio calculates the Fiellers (1954) confidence interval for the ratio of two Gaussian samples by calling ratio.t.test in package mratios, assuming homogeneous variances if var.equal=TRUE. If heterogeneous variances are assumed (setting var.equal=FALSE, the default), the test by Tamhane and Logan (2004) is inverted by solving a quadratic equation according to Fieller, where the estimated ratio is simply plugged in order to get Satterthwaite approximated degrees of freedom. See Hasler and Vonk (2006) for some simulation results.
  • Lognorm.diff calculates the confidence interval for the difference in means of two Lognormal samples, based on general pivotal quantities (Chen and Zhou, 2005); currently, further arguments (...) are not used;
  • Lognorm.ratio calculates the confidence interval for the ratio in means of two Lognormal samples, based on general pivotal quantities (Chen and Zhou, 2005); currently, further arguments (...) are not used;
  • HL.diff calculates the Hodges-Lehmann confidence interval for the difference of locations by calling wilcox.exact in package exactRankTests ;
  • HL.ratio calculates the Hodges-Lehmann-like confidence interval for the ratio of locations by calling wilcox.exact in package exactRankTests for the logarithms of observations;
  • Median.diff calculates a percentile bootstrap confidence interval for the difference of Medians using boot.ci in package boot, the number of bootstrap replications can be set via R=999 (default);
  • Median.ratio calculates a percentile bootstrap confidence interval for the ratio of Medians using boot.ci in package boot, the number of bootstrap replications can be set via R=999 (default);

Values

A list containing:

conf.int
a vector containing the lower and upper confidence limit
estimate
a single named value

References

  • Param.diff uses t.test in stats.
  • Fieller EC (1954): Some problems in interval estimation. Journal of the Royal Statistical Society, Series B, 16, 175-185.
  • Tamhane, AC, Logan, BR (2004): Finding the maximum safe dose level for heteroscedastic data. Journal of Biopharmaceutical Statistics 14, 843-856.
  • Hasler, M, Vonk, R, Hothorn, LA: Assessing non-inferiority of a new treatment in a three arm trial in the presence of heteroscedasticity (submitted).
  • Chen, Y-H, Zhou, X-H (2006): Interval estimates for the ratio and the difference of two lognormal means. Statistics in Medicine 25, 4099-4113.
  • Hothorn, T, Munzel, U: Non-parametric confidence interval for the ratio. Report University of Erlangen, Department Medical Statistics 2002; available via: http://www.imbe.med.uni-erlangen.de/~hothorn/.

Examples

data(sodium)
 
iso<-subset(sodium, Treatment=="xisogenic")$Sodiumcontent
trans<-subset(sodium, Treatment=="transgenic")$Sodiumcontent
 
iso
trans
 
## CI for the difference of means, 
# assuming normal errors and homogeneous variances :
 
thomo<-Param.diff(x=iso, y=trans, var.equal=TRUE)
 
# allowing heterogeneous variances
thetero<-Param.diff(x=iso, y=trans, var.equal=FALSE)
 
 
## Fieller CIs for the ratio of means,
# also assuming normal errors:
 
Fielhomo<-Param.ratio(x=iso, y=trans, var.equal=TRUE)
 
# allowing heterogeneous variances
 
Fielhetero<-Param.ratio(x=iso, y=trans, var.equal=FALSE)
 
 
## Hodges-Lehmann Intervalls for difference and ratios:
 
HLD<-HL.diff(x=iso, y=trans,)
 
# allowing heterogeneous variances
 
HLR<-HL.ratio(x=iso, y=trans,)
 
 
 
MedianD<-Median.diff(x=iso, y=trans,)
 
# allowing heterogeneous variances
 
MedianR<-Median.ratio(x=iso, y=trans,)
 
thomo
thetero
 
Fielhomo
Fielhetero
 
HLD
HLR
 
MedianD
MedianR
 
# # #
 
# Lognormal CIs:
 
x<-rlnorm(n=10, meanlog=0, sdlog=1)
y<-rlnorm(n=10, meanlog=0, sdlog=1)
 
Lognorm.diff(x=x, y=y)
Lognorm.ratio(x=x, y=y)

Documentation reproduced from package pairwiseCI, version 0.1-21. License: GPL