pairwiseCImethodsCont {pairwiseCI} | R Documentation |
Confidence intervals for two sample comparisons of continuous data
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", ...)
HD.diff(x, y, conf.level=0.95, alternative="two.sided", ...)
HD.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;
- HD.diff calculates a percentile bootstrap confidence interval for the difference
of “Harrell-Davis” estimates for location using code copied from hdquantile in package Hmisc
and boot.ci in boot, the number of bootstrap replications can be set
via R=999 (default) ;
- HD.ratio calculates a percentile bootstrap confidence interval for the ratio
of “Harrell-Davis” estimates for location using code copied from hdquantile in package Hmisc
and boot.ci in package boot, the number of bootstrap replications can be set
via R=999 (default);
- 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);
Value
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/.
- HD.diff xxx
- HD.ratio xxx
- Median.diff xxx
- Median.ratio xxx
Examples
##############################################
# Dieldrin example: Two-sample situation:
# The dieldrin example
data(dieldrin)
Ray<-subset(dieldrin, River=="Ray")$dieldrin
Thames<-subset(dieldrin, River=="aThames")$dieldrin
Ray
Thames
## CI for the difference of means,
# assuming normal errors and homogeneous variances :
thomo<-Param.diff(x=Thames, y=Ray, var.equal=TRUE)
# allowing heterogeneous variances
thetero<-Param.diff(x=Thames, y=Ray, var.equal=FALSE)
## Fieller CIs for the ratio of means,
# also assuming normal errors:
Fielhomo<-Param.ratio(x=Thames, y=Ray, var.equal=TRUE)
# allowing heterogeneous variances
Fielhetero<-Param.ratio(x=Thames, y=Ray, var.equal=FALSE)
## Hodges-Lehmann Intervalls for difference and ratios:
HLD<-HL.diff(x=Thames, y=Ray)
# allowing heterogeneous variances
HLR<-HL.ratio(x=Thames, y=Ray)
## Percentile Bootstrap intervals of Harrell-Davis estimators:
HDD<-HD.diff(x=Thames, y=Ray)
# allowing heterogeneous variances
HDR<-HD.ratio(x=Thames, y=Ray)
## Percentile Bootstrap intervals of Medians:
MedianD<-Median.diff(x=Thames, y=Ray)
# allowing heterogeneous variances
MedianR<-Median.ratio(x=Thames, y=Ray)
thomo
thetero
Fielhomo
Fielhetero
HLD
HLR
HDD
HDR
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)
[Package
pairwiseCI version 0.1-19
Index]