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Abstract:
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Why do members of the United States Congress choose to cosponsor legislation proposed by their colleagues and what can we learn from their patterns of cosponsorship? These questions have attracted increased interest among legislative scholars over the past several years, and are, fundamentally, questions about relationships. Unfortunately, most methods of statistical inference with which political scientists are likely to be familiar tend to be ill-suited for the analysis of relational data, where observations are interdependent. We use mixed effects to capture network-type patterns of dependence (e.g., sender- and receiver-specific effects, reciprocity). Explicitly modeling network phenomena allows us to more confidently examine whether various dyadic properties of interest, such as similarities and opportunities for interaction between senators, translate into increased cosponsorship.
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