There is life beyond the statistical significance
- Autores
- Ciapponi, Agustín; Belizan, Jose; Piaggio, Gilda; Yaya, Sanni
- Año de publicación
- 2021
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- This article challenges the “tyranny of P-value” and promote more valuable and applicable interpretations of the results of research on health care delivery. We provide here solid arguments to retire statistical significance as the unique way to interpret results, after presenting the current state of the debate inside the scientific community. Instead, we promote reporting the much more informative confidence intervals and eventually adding exact P-values. We also provide some clues to integrate statistical and clinical significance by referring to minimal important differences and integrating the effect size of an intervention and the certainty of evidence ideally using the GRADE approach. We have argued against interpreting or reporting results as statistically significant or statistically non-significant. We recommend showing important clinical benefits with their confidence intervals in cases of point estimates compatible with results benefits and even important harms. It seems fair to report the point estimate and the more likely values along with a very clear statement of the implications of extremes of the intervals. We recommend drawing conclusions, considering the multiple factors besides P-values such as certainty of the evidence for each outcome, net benefit, economic considerations and values and preferences. We use several examples and figures to illustrate different scenarios and further suggest a wording to standardize the reporting. Several statistical measures have a role in the scientific communication of studies, but it is time to understand that there is life beyond the statistical significance. There is a great opportunity for improvement towards a more complete interpretation and to a more standardized reporting.
Fil: Ciapponi, Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentina
Fil: Belizan, Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentina
Fil: Piaggio, Gilda. Instituto de Efectividad Clínica y Sanitaria; Argentina
Fil: Yaya, Sanni. Imperial College London; Reino Unido. University of Ottawa; Canadá - Materia
-
P-VALUE
STATISTICS
HEALTH CARE DELIVERY - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/175524
Ver los metadatos del registro completo
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There is life beyond the statistical significanceCiapponi, AgustínBelizan, JosePiaggio, GildaYaya, SanniP-VALUESTATISTICSHEALTH CARE DELIVERYhttps://purl.org/becyt/ford/3.3https://purl.org/becyt/ford/3This article challenges the “tyranny of P-value” and promote more valuable and applicable interpretations of the results of research on health care delivery. We provide here solid arguments to retire statistical significance as the unique way to interpret results, after presenting the current state of the debate inside the scientific community. Instead, we promote reporting the much more informative confidence intervals and eventually adding exact P-values. We also provide some clues to integrate statistical and clinical significance by referring to minimal important differences and integrating the effect size of an intervention and the certainty of evidence ideally using the GRADE approach. We have argued against interpreting or reporting results as statistically significant or statistically non-significant. We recommend showing important clinical benefits with their confidence intervals in cases of point estimates compatible with results benefits and even important harms. It seems fair to report the point estimate and the more likely values along with a very clear statement of the implications of extremes of the intervals. We recommend drawing conclusions, considering the multiple factors besides P-values such as certainty of the evidence for each outcome, net benefit, economic considerations and values and preferences. We use several examples and figures to illustrate different scenarios and further suggest a wording to standardize the reporting. Several statistical measures have a role in the scientific communication of studies, but it is time to understand that there is life beyond the statistical significance. There is a great opportunity for improvement towards a more complete interpretation and to a more standardized reporting.Fil: Ciapponi, Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; ArgentinaFil: Belizan, Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; ArgentinaFil: Piaggio, Gilda. Instituto de Efectividad Clínica y Sanitaria; ArgentinaFil: Yaya, Sanni. Imperial College London; Reino Unido. University of Ottawa; CanadáBioMed Central2021-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/175524Ciapponi, Agustín; Belizan, Jose; Piaggio, Gilda; Yaya, Sanni; There is life beyond the statistical significance; BioMed Central; Reproductive Health; 18; 1; 12-2021; 1-81742-4755CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://reproductive-health-journal.biomedcentral.com/articles/10.1186/s12978-021-01131-winfo:eu-repo/semantics/altIdentifier/doi/10.1186/s12978-021-01131-winfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:29:34Zoai:ri.conicet.gov.ar:11336/175524instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:29:35.059CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
There is life beyond the statistical significance |
title |
There is life beyond the statistical significance |
spellingShingle |
There is life beyond the statistical significance Ciapponi, Agustín P-VALUE STATISTICS HEALTH CARE DELIVERY |
title_short |
There is life beyond the statistical significance |
title_full |
There is life beyond the statistical significance |
title_fullStr |
There is life beyond the statistical significance |
title_full_unstemmed |
There is life beyond the statistical significance |
title_sort |
There is life beyond the statistical significance |
dc.creator.none.fl_str_mv |
Ciapponi, Agustín Belizan, Jose Piaggio, Gilda Yaya, Sanni |
author |
Ciapponi, Agustín |
author_facet |
Ciapponi, Agustín Belizan, Jose Piaggio, Gilda Yaya, Sanni |
author_role |
author |
author2 |
Belizan, Jose Piaggio, Gilda Yaya, Sanni |
author2_role |
author author author |
dc.subject.none.fl_str_mv |
P-VALUE STATISTICS HEALTH CARE DELIVERY |
topic |
P-VALUE STATISTICS HEALTH CARE DELIVERY |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/3.3 https://purl.org/becyt/ford/3 |
dc.description.none.fl_txt_mv |
This article challenges the “tyranny of P-value” and promote more valuable and applicable interpretations of the results of research on health care delivery. We provide here solid arguments to retire statistical significance as the unique way to interpret results, after presenting the current state of the debate inside the scientific community. Instead, we promote reporting the much more informative confidence intervals and eventually adding exact P-values. We also provide some clues to integrate statistical and clinical significance by referring to minimal important differences and integrating the effect size of an intervention and the certainty of evidence ideally using the GRADE approach. We have argued against interpreting or reporting results as statistically significant or statistically non-significant. We recommend showing important clinical benefits with their confidence intervals in cases of point estimates compatible with results benefits and even important harms. It seems fair to report the point estimate and the more likely values along with a very clear statement of the implications of extremes of the intervals. We recommend drawing conclusions, considering the multiple factors besides P-values such as certainty of the evidence for each outcome, net benefit, economic considerations and values and preferences. We use several examples and figures to illustrate different scenarios and further suggest a wording to standardize the reporting. Several statistical measures have a role in the scientific communication of studies, but it is time to understand that there is life beyond the statistical significance. There is a great opportunity for improvement towards a more complete interpretation and to a more standardized reporting. Fil: Ciapponi, Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentina Fil: Belizan, Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentina Fil: Piaggio, Gilda. Instituto de Efectividad Clínica y Sanitaria; Argentina Fil: Yaya, Sanni. Imperial College London; Reino Unido. University of Ottawa; Canadá |
description |
This article challenges the “tyranny of P-value” and promote more valuable and applicable interpretations of the results of research on health care delivery. We provide here solid arguments to retire statistical significance as the unique way to interpret results, after presenting the current state of the debate inside the scientific community. Instead, we promote reporting the much more informative confidence intervals and eventually adding exact P-values. We also provide some clues to integrate statistical and clinical significance by referring to minimal important differences and integrating the effect size of an intervention and the certainty of evidence ideally using the GRADE approach. We have argued against interpreting or reporting results as statistically significant or statistically non-significant. We recommend showing important clinical benefits with their confidence intervals in cases of point estimates compatible with results benefits and even important harms. It seems fair to report the point estimate and the more likely values along with a very clear statement of the implications of extremes of the intervals. We recommend drawing conclusions, considering the multiple factors besides P-values such as certainty of the evidence for each outcome, net benefit, economic considerations and values and preferences. We use several examples and figures to illustrate different scenarios and further suggest a wording to standardize the reporting. Several statistical measures have a role in the scientific communication of studies, but it is time to understand that there is life beyond the statistical significance. There is a great opportunity for improvement towards a more complete interpretation and to a more standardized reporting. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-12 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/175524 Ciapponi, Agustín; Belizan, Jose; Piaggio, Gilda; Yaya, Sanni; There is life beyond the statistical significance; BioMed Central; Reproductive Health; 18; 1; 12-2021; 1-8 1742-4755 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/175524 |
identifier_str_mv |
Ciapponi, Agustín; Belizan, Jose; Piaggio, Gilda; Yaya, Sanni; There is life beyond the statistical significance; BioMed Central; Reproductive Health; 18; 1; 12-2021; 1-8 1742-4755 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/https://reproductive-health-journal.biomedcentral.com/articles/10.1186/s12978-021-01131-w info:eu-repo/semantics/altIdentifier/doi/10.1186/s12978-021-01131-w |
dc.rights.none.fl_str_mv |
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openAccess |
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BioMed Central |
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BioMed Central |
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reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
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