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
|
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
|
level |
Confidence interval level. Defaults to |
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)