论文标题
贝叶斯对社会影响的分析
Bayesian Analysis of Social Influence
论文作者
论文摘要
网络影响模型是二进制结果变量的模型，该模型解释了相关单位的结果之间的依赖性。先前扩展了基本影响模型，以提供一系列新的依赖假设，并且由于它与传统的马尔可夫随机场模型的关系，通常被称为自动逻辑参与者 - 属性模型（ALAAM）。我们通过提出一种全面的贝叶斯推理方案来扩展拟合ALAAM的当前方法，该方案支持跨数据子集和缺少数据的存在测试。我们通过三个经验例子说明了程序的不同方面：澳大利亚全男性学校班的男性态度，瑞典学校的教育进步以及澳大利亚社区样本中成年人的未就业。
The network influence model is a model for binary outcome variables that accounts for dependencies between outcomes for units that are relationally tied. The basic influence model was previously extended to afford a suite of new dependence assumptions and because of its relation to traditional Markov random field models it is often referred to as the auto logistic actor-attribute model (ALAAM). We extend on current approaches for fitting ALAAMs by presenting a comprehensive Bayesian inference scheme that supports testing of dependencies across subsets of data and the presence of missing data. We illustrate different aspects of the procedures through three empirical examples: masculinity attitudes in an all-male Australian school class, educational progression in Swedish schools, and un-employment among adults in a community sample in Australia.
