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指数族响应下的试验设计札记AI 解读

Some simple design problems are considered when responses have an exponential family distribution with the difference between ‘treatment’ groups in the canonical parameter being the objective of study. It is shown that normal theory conclusions apply to a possibly surprising extent. The loss from randomizing followed by subsequent stratification is the equivalent of one observation per stratum. For binary data heterogeneity has to be quite large before failure to stratify…

二元序列的回归分析AI 解读

Summary A sequence of 0’s and 1’s is observed and it is suspected that the chance that a particular trial is a 1 depends on the value of one or more independent variables. Tests and estimates for such situations are considered, dealing first with problems in which the independent variable is preassigned and then with independent variables that are functions of the sequence. There is a considerable amount of earlier work, which is reviewed.