Social Scientists rarely take full advantage of the information available in their statistical results. As a consequence, they miss opportunities to present quantities that are of greatest substantive interest for their research and express the appropriate degree of certainty about these quantities. In this article, we offer an approach, built on the technique of statistical simulation, to extract the currently overlooked information from any statistical method and to interpret and present it in a reader-friendly manner. Using this technique requires some expertise, which we try to provide herein, but its application should make the results of quantitative articles more informative and transparent. To illustrate our recommendations, we replicate the results of several published works, showing in each case how the authors' own conclusions can be expressed more sharply and informatively, and, without changing any data or statistical assumptions, how our approach reveals important new information about the research questions at hand. We also offer very easy-to-use Clarify software that implements our suggestions.
You may also be interested in (pdf format) slides used to present this work at a recent short course, an interactive video, and the associated ICPSR Publication Related Archives replication data set (number 1255). This article is in a sense an improved version of Section 5.2 of Unifying Political Methodology: The Likelihood Theory of Statistical Inference (reprinted by University of Michigan Press in 1998; see also a list of corrections). Also available is Zelig software, which works within R, that extends and generalizes Clarify. Also see related research.