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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Understanding and interpreting confidence and credible intervals around effect estimates

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Hespanhol, Luiz [1, 2, 3] ; Vallio, Caio Sain [1] ; Costa, Luciola Menezes [1] ; Saragiotto, Bruno T. [1]
Total Authors: 4
[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
Total Affiliations: 3
Document type: Review article
Source: BRAZILIAN JOURNAL OF PHYSICAL THERAPY; v. 23, n. 4, p. 290-301, JUL-AUG 2019.
Web of Science Citations: 1

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)

FAPESP's process: 16/24217-7 - The effectiveness of a telerehabilitation program for chronic musculoskeletal pain: the e-Rehab program
Grantee:Bruno Tirotti Saragiotto
Support Opportunities: Research Grants - Young Investigators Grants
FAPESP's process: 17/11665-4 - Development and evaluation process of a prevention program on running-related injuries
Grantee:Caio Sain Vallio
Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
FAPESP's process: 16/09220-1 - Development and evaluation process of a prevention program on running-related injuries
Grantee:Luiz Carlos Hespanhol Junior
Support Opportunities: Research Grants - Young Investigators Grants