Bayesian Inference for Comparative Research
The American Political Science Review, (1994)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.
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