
I reflect on the statistical methods of the Christakis–Fowler studies on network‐based contagion of traits by checking the sensitivity of these kinds of results to various alternate specifications and generative mechanisms. Despite the honest efforts of all involved, I remain pessimistic about establishing whether binary health outcomes or product adoptions are contagious if the evidence comes from simultaneously observed data. Copyright © 2012 John Wiley & Sons, Ltd.
FOS: Computer and information sciences, social networks, Behavior, Social Support, Models, Psychological, Statistics - Applications, Applications of statistics to biology and medical sciences; meta analysis, Humans, Applications (stat.AP), social contagion, causal inference
FOS: Computer and information sciences, social networks, Behavior, Social Support, Models, Psychological, Statistics - Applications, Applications of statistics to biology and medical sciences; meta analysis, Humans, Applications (stat.AP), social contagion, causal inference
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 14 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
