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暴露测量误差下超额相对风险回归的联合非参数校正估计AI 解读

Summary Observational epidemiological studies often confront the problem of estimating exposure–disease relationships when the exposure is not measured exactly. We investigate exposure measurement error in excess relative risk regression, which is a widely used model in radiation exposure effect research. In the study cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies a generalized version of the classical…

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光滑拟合优度检验的效率AI 解读

The smooth goodness-of-fit test of Neyman (1937) was generalized to composite hypotheses by Javitz (1975) and Thomas and Pierce (1979). The test statistic is derived, as is its local asymptotic relative efficiency (LARE), which permits its comparison with other quadratic score statistic (QSS) tests, which include a Pearson-type χ2 test. For testing the negative exponential and normal distributions, the smooth test is seen to have greater LARE than the Pearson-type test and…

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回归模型误差分布的拟合优度检验AI 解读

Asymptotic results are given for the problem of testing goodness of fit for any specified distribution of errors in multiple regression models. In particular, the results apply to the case of testing for normality in standard regression and experimental design models. For a very wide class of goodness of fit statistics, in particular those which depend only on the empirical distribution of the residuals, it is shown that the limiting distributions under the null hypothesis…