The Communicability of Graphical Alternatives to Tabular Displays of Statistical Simulation Studies
Identifieur interne : 000525 ( Main/Merge ); précédent : 000524; suivant : 000526The Communicability of Graphical Alternatives to Tabular Displays of Statistical Simulation Studies
Auteurs : Alex R. Cook ; Shanice W. L. TeoSource :
- PLoS ONE ; 2011.
Abstract
Simulation studies are often used to assess the frequency properties and optimality of statistical methods. They are typically reported in tables, which may contain hundreds of figures to be contrasted over multiple dimensions. To assess the degree to which these tables are fit for purpose, we performed a randomised cross-over experiment in which statisticians were asked to extract information from (i) such a table sourced from the literature and (ii) a graphical adaptation designed by the authors, and were timed and assessed for accuracy. We developed hierarchical models accounting for differences between individuals of different experience levels (under- and post-graduate), within experience levels, and between different table-graph pairs. In our experiment, information could be extracted quicker and, for less experienced participants, more accurately from graphical presentations than tabular displays. We also performed a literature review to assess the prevalence of hard-to-interpret design features in tables of simulation studies in three popular statistics journals, finding that many are presented innumerately. We recommend simulation studies be presented in graphical form.
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DOI: 10.1371/journal.pone.0027974
PubMed: 22132184
PubMed Central: 3223202
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Cook</name><affiliation><nlm:aff id="aff1"><addr-line>Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Republic of Singapore</addr-line></nlm:aff><wicri:noCountry code="subfield">Republic of Singapore</wicri:noCountry></affiliation><affiliation><nlm:aff id="aff2"><addr-line>Department of Statistics and Applied Probability, National University of Singapore, Singapore, Republic of Singapore</addr-line></nlm:aff><wicri:noCountry code="subfield">Republic of Singapore</wicri:noCountry></affiliation><affiliation><nlm:aff id="aff3"><addr-line>Program in Health Services and Systems Research, Duke-NUS Graduate Medical School Singapore, National University of Singapore, Singapore, Republic of Singapore</addr-line></nlm:aff><wicri:noCountry code="subfield">Republic of Singapore</wicri:noCountry></affiliation></author><author><name sortKey="Teo, Shanice W L" sort="Teo, Shanice W L" uniqKey="Teo S" first="Shanice W. L." last="Teo">Shanice W. L. 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Teo</name><affiliation><nlm:aff id="aff2"><addr-line>Department of Statistics and Applied Probability, National University of Singapore, Singapore, Republic of Singapore</addr-line></nlm:aff><wicri:noCountry code="subfield">Republic of Singapore</wicri:noCountry></affiliation></author></analytic><series><title level="j">PLoS ONE</title><idno type="e-ISSN">1932-6203</idno><imprint><date when="2011">2011</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Simulation studies are often used to assess the frequency properties and optimality of statistical methods. They are typically reported in tables, which may contain hundreds of figures to be contrasted over multiple dimensions. 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