Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
type="main" xml:id="obes12074-abs-0001"> <title type="main">Abstract</title> <p>Negative binomial estimators are commonly used in estimating models with count-data dependent variables. In this paper, sampling experiments are used to evaluate the performance of these estimators relative to the simpler Poisson estimator in finite-sample situations. The results do not suggest a clear preference for negative binomial estimators in situations in which the underlying dependent variables are overdispersed, unless the researcher is comfortable in assumptions about the precise form of the overdispersion.