Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Failure to properly treat heterogeneity components in longitudinal analyses can result in an incorrect parametrization of the duration model. Estimation bias is not limited to duration dependence but also extends to the structural parameters. This paper uses Monte Carlo methods to examine the finite sample behavior of three estimators for this problem: nonparametric maximum likelihood, maximum penalized likelihood, and the probability simulator. The authors' results on the estimators' finite sample behavior for this class of model add to limited experimental evidence. They highlight the estimators' computational feasibility and point to their relative strengths in empirical duration modeling. Copyright 1994 by MIT Press.