Making the Most of Statistical Analyses: Improving Interpretation and Presentation

@article{citeulike:2534509, abstract = {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 over-looked 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 software that implements our suggestions.}, author = {King, Gary and Tomz, Michael and Wittenberg, Jason }, citeulike-article-id = {2534509}, journal = {American Journal of Political Science}, keywords = {interpretation, presentation, statistics}, number = {2}, pages = {347--361}, posted-at = {2008-03-14 16:58:23}, priority = {0}, title = {Making the Most of Statistical Analyses: Improving Interpretation and Presentation}, url = {http://www.jstor.org/stable/2669316}, volume = {44}, year = {2000} }

TY - JOUR ID - citeulike:2534509 L3 - citeulike-article-id:2534509 TI - Making the Most of Statistical Analyses: Improving Interpretation and Presentation JF - American Journal of Political Science VL - 44 IS - 2 SP - 347 EP - 361 N2 - 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 over-looked 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 software that implements our suggestions. KW - interpretation KW - presentation KW - statistics AU - King, Gary AU - Tomz, Michael AU - Wittenberg, Jason PY - 2000/// UR - http://www.jstor.org/stable/2669316 ER -