Reanalyzing Ultimatum Bargaining—Comparing Nondecreasing Curves Without Shape Constraints
用分层贝叶斯方法估计和比较非递减响应曲线，通过狄利克雷过程先验和马尔可夫链蒙特卡洛计算，重新分析实验者观察是否影响最后通牒博弈的数据，放松了原分析的形状约束。
We employ a hierarchical Bayesian method with exchangeable prior distributions to estimate and compare similar nondecreasing response curves. A Dirichlet process distribution is assigned to each of the response curves as a first stage prior. A second stage prior is then used to model the hyperparameters. We define parameters which will be used to compare the response curves. A Markov chain Monte Carlo method is applied to compute the resulting Bayesian estimates. To illustrate the methodology, we re-examine data from an experiment designed to test whether experimenter observation influences the ultimatum game. A major restriction of the original analysis was the shape constraint that the present technique allows us to greatly relax. We also consider independent priors and use Bayes factors to compare various models.