Wang Bokai, Wu Pan, Kwan Brian, Tu Xin M, Feng Changyong
Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, USA.
Value Institute, Christiana Care Health System, John H Ammon Medical Education Center, Newark, DE, USA.
Shanghai Arch Psychiatry. 2018 Apr 25;30(2):139-143. doi: 10.11919/j.issn.1002-0829.218026.
Simpson's paradox is very prevalent in many areas. It characterizes the inconsistency between the conditional and marginal interpretations of the data. In this paper, we illustrate through some examples how the Simpson's paradox can happen in continuous, categorical, and time-to-event data.
辛普森悖论在许多领域都非常普遍。它体现了数据的条件解释和边际解释之间的不一致性。在本文中,我们通过一些例子来说明辛普森悖论如何在连续数据、分类数据和事件发生时间数据中出现。