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Raw Data Visualization for Common Factorial Designs Using SPSS: A Syntax Collection and Tutorial

Transparency in data visualization is an essential ingredient for scientific communication. The traditional approach of visualizing continuous quantitative data solely in the form of summary statistics (i.e., measures of central tendency and dispersion) has repeatedly been criticized for not reveali...

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Autor principal: Loffing, Florian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9005633/
https://www.ncbi.nlm.nih.gov/pubmed/35432129
http://dx.doi.org/10.3389/fpsyg.2022.808469
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author Loffing, Florian
author_facet Loffing, Florian
author_sort Loffing, Florian
collection PubMed
description Transparency in data visualization is an essential ingredient for scientific communication. The traditional approach of visualizing continuous quantitative data solely in the form of summary statistics (i.e., measures of central tendency and dispersion) has repeatedly been criticized for not revealing the underlying raw data distribution. Remarkably, however, systematic and easy-to-use solutions for raw data visualization using the most commonly reported statistical software package for data analysis, IBM SPSS Statistics, are missing. Here, a comprehensive collection of more than 100 SPSS syntax files and an SPSS dataset template is presented and made freely available that allow the creation of transparent graphs for one-sample designs, for one- and two-factorial between-subject designs, for selected one- and two-factorial within-subject designs as well as for selected two-factorial mixed designs and, with some creativity, even beyond (e.g., three-factorial mixed-designs). Depending on graph type (e.g., pure dot plot, box plot, and line plot), raw data can be displayed along with standard measures of central tendency (arithmetic mean and median) and dispersion (95% CI and SD). The free-to-use syntax can also be modified to match with individual needs. A variety of example applications of syntax are illustrated in a tutorial-like fashion along with fictitious datasets accompanying this contribution. The syntax collection is hoped to provide researchers, students, teachers, and others working with SPSS a valuable tool to move towards more transparency in data visualization.
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spelling pubmed-90056332022-04-14 Raw Data Visualization for Common Factorial Designs Using SPSS: A Syntax Collection and Tutorial Loffing, Florian Front Psychol Psychology Transparency in data visualization is an essential ingredient for scientific communication. The traditional approach of visualizing continuous quantitative data solely in the form of summary statistics (i.e., measures of central tendency and dispersion) has repeatedly been criticized for not revealing the underlying raw data distribution. Remarkably, however, systematic and easy-to-use solutions for raw data visualization using the most commonly reported statistical software package for data analysis, IBM SPSS Statistics, are missing. Here, a comprehensive collection of more than 100 SPSS syntax files and an SPSS dataset template is presented and made freely available that allow the creation of transparent graphs for one-sample designs, for one- and two-factorial between-subject designs, for selected one- and two-factorial within-subject designs as well as for selected two-factorial mixed designs and, with some creativity, even beyond (e.g., three-factorial mixed-designs). Depending on graph type (e.g., pure dot plot, box plot, and line plot), raw data can be displayed along with standard measures of central tendency (arithmetic mean and median) and dispersion (95% CI and SD). The free-to-use syntax can also be modified to match with individual needs. A variety of example applications of syntax are illustrated in a tutorial-like fashion along with fictitious datasets accompanying this contribution. The syntax collection is hoped to provide researchers, students, teachers, and others working with SPSS a valuable tool to move towards more transparency in data visualization. Frontiers Media S.A. 2022-03-30 /pmc/articles/PMC9005633/ /pubmed/35432129 http://dx.doi.org/10.3389/fpsyg.2022.808469 Text en Copyright © 2022 Loffing. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Loffing, Florian
Raw Data Visualization for Common Factorial Designs Using SPSS: A Syntax Collection and Tutorial
title Raw Data Visualization for Common Factorial Designs Using SPSS: A Syntax Collection and Tutorial
title_full Raw Data Visualization for Common Factorial Designs Using SPSS: A Syntax Collection and Tutorial
title_fullStr Raw Data Visualization for Common Factorial Designs Using SPSS: A Syntax Collection and Tutorial
title_full_unstemmed Raw Data Visualization for Common Factorial Designs Using SPSS: A Syntax Collection and Tutorial
title_short Raw Data Visualization for Common Factorial Designs Using SPSS: A Syntax Collection and Tutorial
title_sort raw data visualization for common factorial designs using spss: a syntax collection and tutorial
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9005633/
https://www.ncbi.nlm.nih.gov/pubmed/35432129
http://dx.doi.org/10.3389/fpsyg.2022.808469
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