Description Usage Arguments Details Value Author(s) References See Also Examples
Implements weighted inverse normal and Fisher combination tests for combining p-values for adaptive seamless designs.
1 | combn.test(stage1, stage2, weight = 0.5, method = "invnorm")
|
stage1 |
Output from function |
stage2 |
Output from function |
weight |
Weight indicating how p-values from stages 1 and 2 are combined; default weight is 0.5 indicating equal weighting between stages (0< |
method |
Select combination test method; available options are “ |
The basic ideas of the combination test approach were proposed by Bauer and Kieser (1999) and make use of a combination function (Bauer and Kohne, 1994) to combine stagewise p-values to allow for interim adaptations and the application of the closed test principle (Marcus et al., 1976) to control the overall test size across multiple hypotheses.
method |
Selected method of combining p-values |
zscores |
Z-scores for each hypothesis |
hyp.comb |
A list of matrices indicating the structure of the intersection hypotheses |
weights |
Weights used for each stage |
Nick Parsons (nick.parsons@warwick.ac.uk)
Bauer P, Kieser M. Combining different phases in the development of medical treatments within a single trial. Statistics in Medicine 1999;18:1833-1848.
Bauer P, Kohne K. Evaluation of experiments with adaptive interim analyses. Biometrics 1994;50:1029-1041.
Marcus R, Peritz E, Gabriel KR. On closed testing procedures with special reference to ordered analysis of variance. Biometrika 1976;63:655-660.
Lehmacher W, Wassmer G. Adaptive sample size calculations in group sequential trials. Biometrics 1999;55:1286-1290.
treatsel.sim
, dunnett.test
, hyp.test
, select.rule
, simeans.binormal
1 2 3 | stage1 <- dunnett.test(c(0.75,1.5,2.25))
stage2 <- dunnett.test(c(0.15,1.75,2.15))
combn.test(stage1,stage2,weight=0.5,method="invnorm")
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