twotrials {twotrials}R Documentation

Combined p-value function inference for two trials

Description

This function computes combined p-values, point estimates, and confidence intervals based on two parameter estimates using fixed-effect meta-analysis, the two-trials rule, Edgington's, Fisher's, Pearson's, and Tippett's combination methods

Usage

twotrials(null = 0, t1, t2, se1, se2, alternative = "greater", level = 0.95)

Arguments

null

Null value for which p-values should be computed. Defaults to 0

t1

Parameter estimate from trial 1

t2

Parameter estimate from trial 2

se1

Standard error of the parameter estimate from trial 1

se2

Standard error of the parameter estimate from trial 2

alternative

One-sided alternative hypothesis. Can be either "greater" or "less". Defaults to "greater"

level

Confidence interval level. Defaults to 0.95

Value

Object of class "twotrials", which is a list of the supplied arguments augmented with pfuns and ipfuns (combined and individual p-value functions), mufuns and imufuns (combined and individual estimation functions), and summaries and isummaries (combined and individual confidence intervals, point estimates, p-values, implicit weights) elements

Author(s)

Samuel Pawel

See Also

pEdgington, muEdgington, pMA, muMA, pTippett, muTippett, p2TR, mu2TR, pFisher, muFisher, pPearson, muPearson, plot.twotrials, print.twotrials

Examples

## logRR estimates from RESPIRE trials
twotrials(null = 0, t1 = -0.4942, t2 = -0.1847, se1 = 0.1833, se2 = 0.1738,
          alternative = "less", level = 0.95)

## compute 99.875% CIs instead
twotrials(null = 0, t1 = -0.4942, t2 = -0.1847, se1 = 0.1833, se2 = 0.1738,
          alternative = "less", level = 0.99875)


[Package twotrials version 0.6 Index]