Bayesian analysis of rank data with application to primate intelligence experiments

被引：40

作者：

Johnson, VE

Deaner, RO

van Schaik, CP

机构：

[1] Los Alamos Natl Lab, Los Alamos, NM 87545 USA

[2] Duke Univ, Med Ctr, Dept Neurobiol, Durham, NC 27710 USA

[3] Duke Univ, Dept Biol Anthropol, Durham, NC 27708 USA

来源：

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION | 2002年 / 97卷 / 457期

关键词：

hierarchical Bayes; Markov chain Monte Carlo; meta-analysis; paired-comparisons; Thurstonian model;

D O I：

10.1198/016214502753479185

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：

A model for analyzing rank data obtained from multiple evaluators, possibly using different ranking criteria, is proposed. The model is specified hierarchically within the Bayesian paradigm and includes parameters that represent the probabilities that two items are assigned equal rankings. Also included are parameters that account for the relative precision of rankings obtained from distinct evaluation schemes. The model is illustrated through a meta-analysis of rank data collected to compare the cognitive abilities of various primate genera.

引用

页码：8 / 17

页数：10

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