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Boxplots for grouped and clustered data in toxicology.
Pallmann, Philip; Hothorn, Ludwig A.
Afiliación
  • Pallmann P; Department of Mathematics and Statistics, Lancaster University, Lancaster, LA1 4YF, UK. p.pallmann@lancaster.ac.uk.
  • Hothorn LA; Institute of Biostatistics, Leibniz University Hannover, 30419, Hannover, Germany.
Arch Toxicol ; 90(7): 1631-8, 2016 Jul.
Article en En | MEDLINE | ID: mdl-26438403
The vast majority of toxicological papers summarize experimental data as bar charts of means with error bars. While these graphics are easy to generate, they often obscure essential features of the data, such as outliers or subgroups of individuals reacting differently to a treatment. In particular, raw values are of prime importance in toxicology; therefore, we argue they should not be hidden in messy supplementary tables but rather unveiled in neat graphics in the results section. We propose jittered boxplots as a very compact yet comprehensive and intuitively accessible way of visualizing grouped and clustered data from toxicological studies together with individual raw values and indications of statistical significance. A web application to create these plots is available online.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Toxicología / Gráficos por Computador / Simulación por Computador / Modelos Estadísticos Tipo de estudio: Risk_factors_studies Límite: Animals Idioma: En Revista: Arch Toxicol Año: 2016 Tipo del documento: Article Pais de publicación: Alemania

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Toxicología / Gráficos por Computador / Simulación por Computador / Modelos Estadísticos Tipo de estudio: Risk_factors_studies Límite: Animals Idioma: En Revista: Arch Toxicol Año: 2016 Tipo del documento: Article Pais de publicación: Alemania