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Unintuitive phenomena definition12/8/2023 Pathological Altruism is a groundbreaking new book - the first to explore the negative aspects of altruism and empathy, seemingly uniformly positive traits. Pathologies of altruism and empathy not only underlie health issues, but also a disparate slew of humankind's most troubled features, including genocide, suicide bombing, self-righteous political partisanship, and ineffective philanthropic and social programs that ultimately worsen the situations they are meant to aid. In fact, pathological altruism, in the form of an unhealthy focus on others to the detriment of one's own needs, may underpin some personality disorders. Hyperempathy - an excess of concern for what others think and how they feel - helps explain popular but poorly defined concepts such as codependency. The selflessness of patients with eating abnormalities forms an important aspect of those disorders. Pathologies of empathy, for example, may trigger depression as well as the burnout seen in healthcare professionals. Pathological Altruism presents a number of new, thought-provoking theses that explore a range of hurtful effects of altruism and empathy. Like most good things, however, altruism can be distorted or taken to an unhealthy extreme. These qualities are so highly regarded and embedded in both secular and religious societies that it seems almost heretical to suggest they can cause harm. The benefits of altruism and empathy are obvious. Our findings have important implications to the design of experiments, as the balanced design is proved to be optimal or close to optimal and the need for the complications involved in following an adaptive design for the purpose of increasing the power of tests is therefore questionable. We prove that the optimal allocation according to the Pitman criterion is the balanced allocation and that the optimal allocation according to the Bahadur approach depends on the unknown parameters. Exact calculations reveal that the optimal allocation according to Bahadur is often close to the balanced design, and the powers of both are comparable to the Neyman allocation for small sample sizes and are generally better for large experiments. We consider two different approaches for optimality of designs that are related to Pitman and Bahadur definitions of relative efficiency of tests. The asymptotic justification of this approach is arguable, since it uses the normal approximation in tails where the error in the approximation is larger than the estimated quantity. As the standard deviations are unknown, an adaptive design is often recommended. Many papers use a normal approximation to the power function and claim that Neyman allocation that assigns subjects to treatment groups according to the ratio of the responses' standard deviations, should be used. The target is to find the design that maximizes the power of the relevant test. We consider the classical problem of selecting the best of two treatments in clinical trials with binary response.
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