Summarize the results from the powerBuyseTest function.
# S4 method for S4BuysePower
summary(
object,
print = TRUE,
statistic = NULL,
endpoint = NULL,
order.Hprojection = NULL,
transformation = NULL,
legend = TRUE,
col.rep = FALSE,
digit = 4
)output of powerBuyseTest
[logical] Should the table be displayed?.
[character] statistic relative to which the power should be computed:
"netBenefit" displays the net benefit, as described in Buyse (2010) and Peron et al. (2016)),
"winRatio" displays the win ratio, as described in Wang et al. (2016),
"mannWhitney" displays the proportion in favor of the treatment (also called Mann-Whitney parameter), as described in Fay et al. (2018).
Default value read from BuyseTest.options().
[character vector] the endpoints to be displayed: must be the name of the endpoint followed by an underscore and then by the threshold.
[integer 1,2] the order of the H-project to be used to compute the variance of the net benefit/win ratio.
[logical] should the CI be computed on the logit scale / log scale for the net benefit / win ratio and backtransformed.
[logical] should explainations about the content of each column be displayed?
[logical] should the number of successful simulations be displayed?
[integer vector] the number of digit to use for printing the counts and the delta.
On the GPC procedure: Marc Buyse (2010). Generalized pairwise comparisons of prioritized endpoints in the two-sample problem. Statistics in Medicine 29:3245-3257 On the win ratio: D. Wang, S. Pocock (2016). A win ratio approach to comparing continuous non-normal outcomes in clinical trials. Pharmaceutical Statistics 15:238-245 On the Mann-Whitney parameter: Fay, Michael P. et al (2018). Causal estimands and confidence intervals asscoaited with Wilcoxon-Mann-Whitney tests in randomized experiments. Statistics in Medicine 37:2923-2937 \
powerBuyseTest for performing a simulation study for generalized pairwise comparison.