Abstract
Regression analysis in comparative research suffers from
two distinct problems of statistical inference. First,
because the data constitute all the available observations
from a population, conventional inference based on the
long-run behavior of a repeatable data mechanism is not
appropriate. Second, the small and collinear data sets of
comparative research yield imprecise estimates of the
effects of explanatory variables. We describe a Bayesian
approach to statistical inference that provides a unified
solution to these two problems. This approach is
illustrated in a comparative analysis of unionization.
Users
Please
log in to take part in the discussion (add own reviews or comments).