Understanding and interpreting confidence and credible intervals around effect estimates

Autor(es)

Hespanhol, Luiz ^{[1, 2, 3]} ; Vallio, Caio Sain ^[1] ; Costa, Luciola Menezes ^[1] ; Saragiotto, Bruno T. ^[1]

Afiliação do(s) autor(es)

^[1] Univ Cidade Sao Paulo UNICID, Masters & Doctoral Programs Phys Therapy, Rua Cesario Galen, 448 Tatuape, BR-03071000 Sao Paulo, SP - Brazil

^[2] VU Univ Med Ctr VUmc, Amsterdam Publ Hlth Res Inst APH, Dept Publ & Occupat Hlth, Amsterdam - Netherlands

^[3] Vrije Univ Amsterdam Med Ctr, IOC Res Ctr, Acad Med Ctr, ACHSS, Amsterdam - Netherlands

• Tipo de documento: Artigo de Revisão
• Fonte: BRAZILIAN JOURNAL OF PHYSICAL THERAPY; v. 23, n. 4, p. 290-301, JUL-AUG 2019.
• Citações Web of Science: 1

Resumo

Introduction: Reporting confidence intervals in scientific articles is important and relevant for evidence-based practice. Clinicians should understand confidence intervals in order to deter mine if they can realistically expect results similar to those presented in research studies when they implement the scientific evidence in clinical practice. The aims of this masterclass are: (1) to discuss confidence intervals around effect estimates; (2) to understand confidence inter vats estimation (frequentist and Bayesian approaches); and (3) to interpret such uncertainty measures. Content: Confidence intervals are measures of uncertainty around effect estimates. Interpretation of the frequentist 95% confidence interval: we can be 95% confident that the true (unknown) estimate would lie within the lower and upper limits of the interval, based on hypothesized repeats of the experiment. Many researchers and health professionals oversimplify the interpretation of the frequentist 95% confidence interval by dichotomizing it in statistically significant or non-statistically significant, hampering a proper discussion on the values, the width (precision) and the practical implications of such interval. Interpretation of the Bayesian 95% confidence interval (which is known as credible interval): there is a 95% probability that the true (unknown) estimate would lie within the interval, given the evidence provided by the observed data. Conclusions: The use and reporting of confidence intervals should be encouraged in all scientific articles. Clinicians should consider using the interpretation, relevance and applicability of confidence intervals in real-world decision-making. Training and education may enhance knowledge and skills related to estimating, understanding and interpreting uncertainty measures, reducing the barriers for their use under either frequentist or Bayesian approaches. (C) 2018 Published by Elsevier Editora Ltda. on behalf of Associacao Brasileira de Pesquisa e Pos-Graduacao em Fisioterapia. (AU)

• Processo FAPESP: 16/24217-7 - A efetividade de um programa de tele-reabilitação para o tratamento da dor crônica musculoesquelética: programa e-Rehab
• Beneficiário: Bruno Tirotti Saragiotto
• Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores
• Processo FAPESP: 17/11665-4 - Avaliação do processo de implementação de um programa de prevenção de lesões relacionadas à corrida
• Beneficiário: Caio Sain Vallio
• Modalidade de apoio: Bolsas no Brasil - Doutorado Direto
• Processo FAPESP: 16/09220-1 - Avaliação do processo de desenvolvimento e implementação de um programa de prevenção de lesões da corrida
• Beneficiário: Luiz Carlos Hespanhol Junior
• Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores