Literature DB >> 26356927

Visualizing Statistical Mix Effects and Simpson's Paradox.

Zan Armstrong, Martin Wattenberg.   

Abstract

We discuss how "mix effects" can surprise users of visualizations and potentially lead them to incorrect conclusions. This statistical issue (also known as "omitted variable bias" or, in extreme cases, as "Simpson's paradox") is widespread and can affect any visualization in which the quantity of interest is an aggregated value such as a weighted sum or average. Our first contribution is to document how mix effects can be a serious issue for visualizations, and we analyze how mix effects can cause problems in a variety of popular visualization techniques, from bar charts to treemaps. Our second contribution is a new technique, the "comet chart," that is meant to ameliorate some of these issues.

Entities:  

Mesh:

Year:  2014        PMID: 26356927     DOI: 10.1109/TVCG.2014.2346297

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  1 in total

1.  The value of the atherogenic index of plasma in non-obese people with non-alcoholic fatty liver disease: a secondary analysis based on a cross-sectional study.

Authors:  Bu-Yuan Dong; Yu-Qing Mao; Zheng-Yang Li; Fu-Jun Yu
Journal:  Lipids Health Dis       Date:  2020-06-23       Impact factor: 3.876

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.