Errors-in-variables beta regression models

被引:16
|
作者
Carrasco, Jalmar M. F. [1 ]
Ferrari, Silvia L. P. [2 ]
Arellano-Valle, Reinaldo B. [3 ]
机构
[1] Univ Fed Bahia, Dept Estat, Salvador, BA, Brazil
[2] Univ Sao Paulo, Dept Estat, BR-05508090 Sao Paulo, SP, Brazil
[3] Pontificia Univ Catolica Chile, Dept Estat, Santiago, Chile
基金
巴西圣保罗研究基金会;
关键词
asymptotic confidence interval; arcsine transformation; Wald method and adjusted Wald methods; continuity correction; Wilson score method; Jeffreys' method; CALIBRATION;
D O I
10.1080/02664763.2014.881784
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
This paper evaluates 29 methods for obtaining a two-sided confidence interval for a binomial proportion (16 of which are new proposals) and comes to the conclusion that: Wilson's classic method is only optimal for a confidence of 99%, although generally it can be applied when n >= 50; for a confidence of 95% or 90%, the optimal method is the one based on the arcsine transformation (when this is applied to the data incremented by 0.5), which behaves in a very similar manner to Jeffreys' Bayesian method. A simpler option, though not so good as those just mentioned, is the classic-adjusted Wald method of Agresti and Coull.
引用
收藏
页码:1530 / 1547
页数:18
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