Generalized Confidence Intervals
将置信区间的定义推广，使其能在不等方差等条件下构造精确置信区域，并应用于两指数均值差和混合模型方差分量，同时给出广义p值的重复抽样性质，解决Pratt悖论。
Abstract The definition of a confidence interval is generalized so that problems such as constructing exact confidence regions for the difference in two normal means can be tackled without the assumption of equal variances. Under certain conditions, the extended definition is shown to preserve a repeated sampling property that a practitioner expects from exact confidence intervals. The proposed procedure is also applied to the problem of constructing confidence intervals for the difference in two exponential means and for variance components in mixed models. A repeated sampling property of generalized p values is also given. With this characterization one can carry out fixed level tests of parameters of continuous distributions on the basis of generalized p values. Finally, Pratt's paradox is revisited, and a procedure that resolves the paradox is given.