Blinded sample size re-estimation in equivalence testing

Some Notes on Blinded Sample Size Re-Estimation

This note investigates a number of scenarios in which unadjusted testing following a blinded sample size re-estimation leads to type I error violations. For superiority testing, this occurs in certain small-sample borderline cases. We discuss a number of alternative approaches that keep the type I error rate. The paper also gives a reason why the type I error inflation in the superiority context might have been missed in previous publications and investigates why it is more marked in case of non-inferiority testing.

Equivalence testing for functional data with an application to comparing pulmonary function devices

Equivalence testing for scalar data has been well addressed in the literature, however, the same cannot be said for functional data. The resultant complexity from maintaining the functional structure of the data, rather than using a scalar transformation to reduce dimensionality, renders the existing literature on equivalence testing inadequate for the desired inference. We propose a framework for equivalence testing for functional data within both the frequentist and Bayesian paradigms. This framework combines extensions of scalar methodologies with new methodology for functional data. Our fr…

在隐私约束下等价性检验

Equivalence Testing Under Privacy Constraints

本文提出在隐私保护下进行等价性检验的新方法，通过模拟校准解决有限样本分布难以解析的问题，确保在隐私预算增加时维持显著性错误控制并保持统计功效。

克服模型不确定性——等价性检验如何从模型平均中获益

Overcoming model uncertainty -- how equivalence tests can benefit from model averaging

本文针对回归模型不确定下的组间等价性检验问题，提出基于平滑AIC权重模型平均的灵活检验方法，利用置信区间与假设检验的对偶性构建检验程序，并通过模拟和毒理学基因表达时间响应案例验证其有效性。

Testing for equivalence: an intersection-union permutation solution

The notion of testing for equivalence of two treatments is widely used in clinical trials, pharmaceutical experiments,bioequivalence and quality control. It is essentially approached within the intersection-union (IU) principle. According to this principle the null hypothesis is stated as the set of effects lying outside a suitably established interval and the alternative as the set of effects lying inside that interval. The solutions provided in the literature are mostly based on likelihood techniques, which in turn are rather difficult to handle, except for cases lying within the regular exp…

Outperformance Portfolio Optimization via the Equivalence of Pure and Randomized Hypothesis Testing

We study the portfolio problem of maximizing the outperformance probability over a random benchmark through dynamic trading with a fixed initial capital. Under a general incomplete market framework, this stochastic control problem can be formulated as a composite pure hypothesis testing problem. We analyze the connection between this pure testing problem and its randomized counterpart, and from latter we derive a dual representation for the maximal outperformance probability. Moreover, in a complete market setting, we provide a closed-form solution to the problem of beating a leveraged exchang…