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*A focus on normal theory linking average power, expected power,
predictive power, assurance, conditional Bayesian power and
Bayesian power. *Extensions of the concepts to binomial, and
time-to-event outcomes and non-inferiority trials *An investigation
into the upper bound on average power, assurance and Bayesian power
based on the prior probability of a positive treatment effect
*Application of assurance to a series of trials in a development
program and an introduction of the assurance of an individual trial
conditional on the positive outcome of an earlier trial in the
program, or to the successful outcome of an interim analysis *Prior
distribution of power and sample size *Extension of the basic
approach to proof-of-concept trials with dual success criteria
*Investigation of the connection between conditional and predictive
power at an interim analysis and power and assurance *Introduction
of the idea of surety in sample sizing of clinical trials based on
the width of the confidence intervals for the treatment effect, and
an unconditional version.
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