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Last data update: 2014.03.03

R: Data analysis with an individual testing procedure in the...

indiv.1m.analysis

R Documentation

Data analysis with an individual testing procedure in the context of multiple continuous endpoints

Description

This function aims at analysing some multiple continuous endpoints with an individual testing procedure. This method, based on Union-Intersection test procedure, allows one to take into account the correlations between the different endpoints in the analysis.

Usage

indiv.1m.analysis(method, XC, XT, varX = NULL, alpha = 0.05,
alternative = "two.sided", n = NULL)

Arguments

`method`	description of the covariance matrix estimation. Two choices are possible: "Unknown" (normality assumption and unknown covariance matrix) and "Asympt" (asymptotic context).
`XC`	matrix of the outcomes for the control group.
`XT`	matrix of the outcomes for the test group.
`varX`	covariance matrix. Should be provided when 'method' = 'Known'.
`alpha`	value which correponds to the chosen Type-I error rate bound.
`alternative`	character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less".
`n`	NULL. Sample size of a group, computed from `XC`.

Value

`UnAdjPvalue`	unadjusted p-values.
`AdjPvalue`	corrected p-values.

Author(s)

P. Lafaye de Micheaux, B. Liquet and J. Riou

References

Lafaye de Micheaux P., Liquet B., Marque S., Riou J. (2014). Power and Sample Size Determination in Clinical Trials With Multiple Primary Continuous Correlated Endpoints, Journal of Biopharmaceutical Statistics, 24, 378–397.

Examples

# Calling the data
data(data.sim)

# Data analysis for the individual method
n <- nrow(data) / 2 

XC <- data[1:n, 1:3]
XT <- data[(n + 1):(2 * n), 1:3]

indiv.1m.analysis(method = "UnKnown", XC = XC, XT = XT)