"Contagion effects, also known as peer effects or social influence process, refer to the phenomenon whereby people tend to assimilate the behavior of those with whom they have interaction in a social network. With the availability of longitudinal social network data, studies of contagion effects have become more and more central to social science, with many applications in the field of education, such as the diffusion of innovation, change of health behaviors, academic outcomes among adolescents, and the implementation of practices among teachers (Valente, 1995, 1996; Christakis et al., 2007, 2008; Sacerdote, 2000; Frank et al, 2004). However, contagion effects are usually difficult to identify as they are often entangled with other factors such as homophily in the selection process, an individual's preference for the same social settings, etc. Methods currently available either do not solve these problems or require strong assumptions. Furthermore, there is still a significant degree of misconception about why identifying contagion effects is a problem, and when these methods should be applied. For this dissertation, in the first chapter I will clarify why and when we will encounter problems identifying contagion effects. Specifically I will frame this in terms of an omitted variable bias problem; and then I will explore the magnitude of bias in the estimation of contagion effects in various situations, and possible remedies under an OLS framework. In the second chapter I will propose some alternative estimation methods that have the potential to correctly identify contagion effects under weaker assumptions when there are unobserved variables present. In the third chapter I will propose a set of simulation-based sensitivity analysis methods that can test the robustness of inferences made in social network analysis, especially inferences about contagion effects."--Page ii.
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