Bayesian analysis of social influence
Bayesian analysis of social influence
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DOI：
10.1111/rssa.12844
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发表时间：
2020-06
期刊：
影响因子：
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通讯作者：
J. Koskinen;G. Daraganova
中科院分区：
文献类型：
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作者：
J. Koskinen;G. Daraganova
网络影响力模型是一个二元结果变量模型，它解释了关系紧密的单位的结果之间的依赖关系。基本影响模型以前被扩展为提供一套新的依赖性假设，并且由于其与传统马尔可夫随机场模型的关系，它通常被称为自动逻辑因素-属性模型（ALAAM）。我们提出了一个全面的贝叶斯推理方案，支持跨数据子集的依赖性测试和缺失数据的存在下，目前的方法来拟合ALAAM扩展。我们说明了不同方面的程序通过三个实证的例子：男性气质的态度在全男性的澳大利亚学校类，在瑞典学校的教育进展，在澳大利亚的社区样本中的成年人失业。
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 unemployment among adults in a community sample in Australia.