Ratios of Coefficients in the General Linear Model
Angina pectoris data
ASAT data
Creates numerator and denominator contrast matrices for ratio-based hy...
Simultaneous confidence intervals for ratios of linear combinations of...
Point and variance estimation for quantiles of independent groups of s...
Simultaneous confidence intervals for contrasts of quantiles
mratios
Sample size computation in simultaneous tests for ratios of means
Plot output for sci.ratio and sci.ratio.gen
Print function for sci.ratio objects
Print out the results of simtest.ratio
Body weight of rats in a toxicity study
Simultaneous confidence intervals for ratios of coefficients in the ge...
Simultaneous confidence intervals for ratios of linear combinations of...
Approximate simultaneous confidence intervals for ratios of means when...
Simultaneous tests for ratios of normal means
Approximate simultaneous tests for ratios of normal means with heterog...
Slope ratio assay of panthotenic acid contents in plant tissues
Summary function for sci.ratio
Summary function for simtest.ratio
t-test for the ratio of two means
Performs (simultaneous) inferences for ratios of linear combinations of coefficients in the general linear model, linear mixed model, and for quantiles in a one-way layout. Multiple comparisons and simultaneous confidence interval estimations can be performed for ratios of treatment means in the normal one-way layout with homogeneous and heterogeneous treatment variances, according to Dilba et al. (2007) <https://cran.r-project.org/doc/Rnews/Rnews_2007-1.pdf> and Hasler and Hothorn (2008) <doi:10.1002/bimj.200710466>. Confidence interval estimations for ratios of linear combinations of linear model parameters like in (multiple) slope ratio and parallel line assays can be carried out. Moreover, it is possible to calculate the sample sizes required in comparisons with a control based on relative margins. For the simple two-sample problem, functions for a t-test for ratio-formatted hypotheses and the corresponding confidence interval are provided assuming homogeneous or heterogeneous group variances.