The inclusion of Bayes factor and the conversion of effect size in anesthesiology and reanimation research

Ramos-Vera, C.

doi:10.1016/j.redare.2021.04.005

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"apellidos" => "Ramos-Vera" "email" => array:1 [ 0 => "cristony_777@hotmail.com" ] "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "*" "identificador" => "cor0005" ] ] ] ] "afiliaciones" => array:1 [ 0 => array:2 [ "entidad" => "Área de investigación, Facultad de Ciencias de la Salud, Universidad Cesar Vallejo, Lima, Peru" "identificador" => "aff0005" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "La inclusión del factor Bayes y la conversión del tamaño de efecto en la investigación en anestesiología y reanimación" ] ] "textoCompleto" => "La presente investigación no ha recibido ayudas específicas provenientes de agencias del sector público, sector comercial o entidades sin ánimo de lucroIn number 8 of volume 67 of this journal, an important study was published reporting a statistically significant correlation between acute renal failure and risk of mortality in the intensive care unit in 270 critically ill patients with COVID-19. This study in question was a significance/hypothesis testing study (p<0.05) based on calculating the odds ratio (OR).<a class="elsevierStyleCrossRef" href="#bib0005">1</a>The importance replicating hypothesis testing studies (p<0.05) in clinical research cannot be overstressed, and researchers should be encouraged to test the reproducibility of conclusive study findings in future anaesthesiology and resuscitation using Bayesian inference.<a class="elsevierStyleCrossRefs" href="#bib0010">2,3</a>This can be done using the Bayes factor (BF), which quantifies the degree to which the data are more likely under one model versus another (null hypothesis vs. alternative hypothesis).<a class="elsevierStyleCrossRefs" href="#bib0010">2,3</a> This allowed us to reanalyse the significant finding reported by Ferrando et al.<a class="elsevierStyleCrossRef" href="#bib0005">1</a> and quantify the degree to which the data support either the null hypothesis or the alternative hypothesis beyond the dichotomous interpretation of the rejection or acceptance of the null hypothesis.<a class="elsevierStyleCrossRefs" href="#bib0010">2,3</a> Statistical replication of significant findings through BF can strengthen the practical credibility of articles in this journal (clinical trials, interventions and treatments, among others) that is required when Bayesian inference reports conclusive (strong) or superior (FB10>10) evidence, based on Jeffreys’ classification of BF values<a class="elsevierStyleCrossRef" href="#bib0020">4</a> as weak, moderate, strong and very strong (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>).<elsevierMultimedia ident="tbl0005"></elsevierMultimedia>The purpose of this letter is to report a simple example of Bayesian reanalysis to determine the degree of probative strength of the statistical hypotheses. Therefore, the OR (2,468) was first converted to an effect size (r) using the Lenhard and Lenhard online calculator,<a class="elsevierStyleCrossRef" href="#bib0025">5</a> which returned a value of r=0.242, and the sample size (270) was also defined for Bayesian replication.<a class="elsevierStyleCrossRef" href="#bib0010">2</a> This method considers 2 interpretations: BF10 (proving the alternative hypothesis) and BF01 (proving the null hypothesis), with a 95% confidence interval (CI).<a class="elsevierStyleCrossRefs" href="#bib0010">2,3</a> The BF results are: BF10=233 and BF01=0.004 with a 95% CI of 0.125–0.350, which supported the significant finding reported by Ferrando et al.<a class="elsevierStyleCrossRef" href="#bib0005">1</a> with very strong evidence in favour of the alternative hypothesis (correlation). Likewise, the size of the maximum BF (maxFB10=483.8) supports the robustness of the reported estimates.BF is a useful statistical method that can make a practical contribution to decision-making by confirming the conclusiveness of reported results.FundingThe authors declare that they have not received specific aid from agencies in the public sector, commercial sector or non-profit entities.Conflict of interestsThe authors have no conflict of interest to declare." "textoCompletoSecciones" => array:1 [ "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0005" "titulo" => "Funding" ] 1 => array:2 [ "identificador" => "sec0010" "titulo" => "Conflict of interests" ] 2 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "Please cite this article as: Ramos-Vera C, La inclusión del factor Bayes y la conversión del tamaño de efecto en la investigación en anestesiología y reanimación, Revista Española de Anestesiología y Reanimación. 2022;69:313–314." ] ] "multimedia" => array:1 [ 0 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0030" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "Based on Jeffreys.<a class="elsevierStyleCrossRef" href="#bib0020">4</a>" "tablatextoimagen" => array:1 [ 0 => array:1 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">>30 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Very strong \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Alternative hypothesis \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10–30 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Strong \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Alternative hypothesis \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.1–10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Moderate \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Alternative hypothesis \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.1–3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Weak \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Alternative hypothesis \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">No evidence \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.3–0.99 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Weak \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Null hypothesis \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.3–0.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Moderate \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Null hypothesis \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.1–0.03 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Strong \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Null hypothesis \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><0.03 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Very strong \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Null hypothesis \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] ] ] ] "descripcion" => array:1 [ "en" => "Interpretation of Bayes factor values." ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:5 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Características, evolución clínica y factores asociados a la mortalidad en UCI de los pacientes críticos infectados por SARS-CoV-2 en España: estudio prospectivo, de cohorte y multicéntrico" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "C. Ferrando" 1 => "R. Mellado-Artigas" 2 => "A. Gea" 3 => "E. Arruti" 4 => "C. Aldecoa" 5 => "A. Bordell" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.redar.2020.07.003" "Revista" => array:6 [ "tituloSerie" => "Rev Esp Anestesiol Reanim." "fecha" => "2020" "volumen" => "67" "numero" => "8" "paginaInicial" => "425" "paginaFinal" => "437" ] ] ] ] ] ] 1 => array:3 [ "identificador" => "bib0010" "etiqueta" => "2" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Bayesian reanalyses from summary statistics: a guide for academic consumers" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:5 [ 0 => "A. Ly" 1 => "A. Raj" 2 => "A. Etz" 3 => "Q.F. Gronau" 4 => "E.J. Wagenmakers" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1177/2515245918779348" "Revista" => array:6 [ "tituloSerie" => "Adv Meth Pract Psychol Sci." "fecha" => "2018" "volumen" => "1" "numero" => "3" "paginaInicial" => "367" "paginaFinal" => "374" ] ] ] ] ] ] 2 => array:3 [ "identificador" => "bib0015" "etiqueta" => "3" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Bayesian benefits with JASP" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:2 [ 0 => "M. Marsmamn" 1 => "E.J. Wagenmakers" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1080/17405629.2016.1259614" "Revista" => array:6 [ "tituloSerie" => "Eur J Dev Psychol." "fecha" => "2017" "volumen" => "14" "numero" => "5" "paginaInicial" => "545" "paginaFinal" => "555" ] ] ] ] ] ] 3 => array:3 [ "identificador" => "bib0020" "etiqueta" => "4" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Theory of probability" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:1 [ 0 => "H. Jeffreys" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Libro" => array:3 [ "fecha" => "1961" "editorial" => "Oxford University Press" "editorialLocalizacion" => "Oxford" ] ] ] ] ] ] 4 => array:3 [ "identificador" => "bib0025" "etiqueta" => "5" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Calculation of effect sizes" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:2 [ 0 => "W. Lenhard" 1 => "A. Lenhard" ] ] ] ] ] "host" => array:2 [ 0 => array:1 [ "Libro" => array:3 [ "fecha" => "2016" "editorial" => "Psychometrica" "editorialLocalizacion" => "Dettelbach, Alemania" ] ] 1 => array:1 [ "WWW" => array:1 [ "link" => "https://www.psychometrica.de/effect_size.html" ] ] ] ] ] ] ] ] ] ] ] "idiomaDefecto" => "en" "url" => "/23411929/0000006900000005/v1_202206100555/S2341192922000841/v1_202206100555/en/main.assets" "Apartado" => array:4 [ "identificador" => "66474" "tipo" => "SECCION" "en" => array:2 [ "titulo" => "Letter to the Director" "idiomaDefecto" => true ] "idiomaDefecto" => "en" ] "PDF" => "https://static.elsevier.es/multimedia/23411929/0000006900000005/v1_202206100555/S2341192922000841/v1_202206100555/en/main.pdf?idApp=UINPBA00004N&text.app=https://www.elsevier.es/" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2341192922000841?idApp=UINPBA00004N"]

ISSN: 2341-1929

Revista Española de Anestesiología y Reanimación (REDAR) -the Spanish Journal of Anesthesiology and Resuscitation- is the scientific body of the Spanish Society of Anesthesiology, Resuscitation and Pain Therapy. This is a monthly journal (10 issues) that publishes scientific articles of all areas within its specialty: clinical anesthesia, resuscitation-intensive medicine and critical care, diagnosis and treatment of acute and chronic pain, urgent care and emergencies and studies on basic science and related fields. The journal accepts work in both Spanish and English.

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Impact factor

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Impact factor 2023

0.9

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1.8

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SJR 2023

0.239

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SNIP 2023

362

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Vol. 69. Issue 5.

Pages 313-314 (May 2022)

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