Practical considerations of the jackknife estimator of variance for generalized estimating equations
作者： Andreas Ziegler
DOI: 10.1007/BF02925276
关键词: Jackknife resampling 、 Estimator 、 Mean squared error 、 Efficiency 、 Minimum-variance unbiased estimator 、 Efficient estimator 、 Bias of an estimator 、 Variance function 、 Mathematics 、 Statistics 、 Statistics, Probability and Uncertainty 、 Statistics and Probability
摘要: Lipsitz, Dear and Zhao (1994) proposed a “one-step” Jackknife estimator of the variance based on Wu's (1986) jackknife showed its asymptotic equivalence to robust White (1982) Liang Zeger (1986). In this paper an asymptotically equivalent is which avoids Newton-Raphson or Fisher scoring step by Zhao. Hence, summation in univariate models can be avoided.
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