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《提高元分析与元回归中基于似然的推断准确性》勘误
Biometrika (2017) 104, pp. 489–96 In equation (3), should be replaced by . The middle expressions in the equations for sψ(θ) and s*ψ (θ) in (4) and (7), respectively, should be divided by 2. The authors are grateful to S. Kyriakou for bringing these errors to their attention.
提高元分析与元回归中似然推断的准确性
Summary Random-effects models are frequently used to synthesize information from different studies in meta-analysis. While likelihood-based inference is attractive both in terms of limiting properties and of implementation, its application in random-effects meta-analysis may result in misleading conclusions, especially when the number of studies is small to moderate. The current paper shows how methodology that reduces the asymptotic bias of the maximum likelihood estimator…
指数族非线性模型中的偏差缩减
In Firth (1993, Biometrika) it was shown how the leading term in the asymptotic bias of the maximum likelihood estimator is removed by adjusting the score vector, and that in canonical-link generalized linear models the method is equivalent to maximizing a penalized likelihood that is easily implemented via iterative adjustment of the data. Here a more general family of bias-reducing adjustments is developed for a broad class of univariate and multivariate generalized…