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

来源：

JOURNAL OF APPLIED STATISTICS | 2014年 / 41卷 / 07期

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

页码：1530 / 1547

页数：18

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