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Gavin Stewart

Showing results (41-50 of 70) with videos related to

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Journal of Clinical Epidemiology|November 10, 2022
Quasi-experiments are a valuable source of evidence about effects of interventions, programs and policies: commentary from the Campbell Collaboration Study Design and Bias Assessment Working GroupHugh Sharma Waddington, David B Wilson, Terri Pigott, et al.
Pharmacology & Therapeutics|January 31, 2025
Biased agonism in peptide-GPCRs: A structural perspectiveTharindunee Jayakody, Dinath Kavishka Budagoda, Krishan Mendis, et al.
Campbell Systematic Reviews|October 8, 2024
Campbell Standards: Modernizing Campbell's Methodologic Expectations for Campbell Collaboration Intervention Reviews (MECCIR)Ariel M Aloe, Omar Dewidar, Emily A Hennessy, et al.
Campbell Systematic Reviews|June 12, 2026
Risk of Bias in Experiments, Quasi-Experiments and Natural Experiments Across Disciplines: Discussion Paper and Assessment FrameworkHugh Sharma Waddington, David B Wilson, Terri Pigott, et al.
JAMA|April 29, 2015
Preferred Reporting Items for Systematic Review and Meta-Analyses of individual participant data: the PRISMA-IPD StatementLesley A Stewart, Mike Clarke, Maroeska Rovers, et al.
Pain|April 26, 2022
Investigating the veracity of a sample of divergent published trial data in spinal painNeil E O'Connell, R Andrew Moore, Gavin Stewart, et al.
Journal of Clinical Epidemiology|March 2, 2023
Effective quality control in the medical literature: investigation and retraction vs inactionAmanda C de C Williams, Leslie Hearn, R Andrew Moore, et al.
Pain|March 20, 2023
Reply to MonticoneNeil Edward O'Connell, R Andrew Moore, Gavin Stewart, et al.
The Journal of Pain|July 15, 2023
Trials We Cannot Trust: Investigating Their Impact on Systematic Reviews and Clinical Guidelines in Spinal PainNeil O'Connell, R Andrew Moore, Gavin Stewart, et al.
Health Technology Assessment (Winchester, England)|October 5, 2024
Antidepressants for pain management in adults with chronic pain: a network meta-analysisHollie Birkinshaw, Claire Friedrich, Peter Cole, et al.
Pageof 7

Showing results (41-50 of 70) with videos related to

Sort By:
Pageof 7
Journal of Clinical Epidemiology|November 10, 2022
Quasi-experiments are a valuable source of evidence about effects of interventions, programs and policies: commentary from the Campbell Collaboration Study Design and Bias Assessment Working GroupHugh Sharma Waddington, David B Wilson, Terri Pigott, et al.
Pharmacology & Therapeutics|January 31, 2025
Biased agonism in peptide-GPCRs: A structural perspectiveTharindunee Jayakody, Dinath Kavishka Budagoda, Krishan Mendis, et al.
Campbell Systematic Reviews|October 8, 2024
Campbell Standards: Modernizing Campbell's Methodologic Expectations for Campbell Collaboration Intervention Reviews (MECCIR)Ariel M Aloe, Omar Dewidar, Emily A Hennessy, et al.
Campbell Systematic Reviews|June 12, 2026
Risk of Bias in Experiments, Quasi-Experiments and Natural Experiments Across Disciplines: Discussion Paper and Assessment FrameworkHugh Sharma Waddington, David B Wilson, Terri Pigott, et al.
JAMA|April 29, 2015
Preferred Reporting Items for Systematic Review and Meta-Analyses of individual participant data: the PRISMA-IPD StatementLesley A Stewart, Mike Clarke, Maroeska Rovers, et al.
Pain|April 26, 2022
Investigating the veracity of a sample of divergent published trial data in spinal painNeil E O'Connell, R Andrew Moore, Gavin Stewart, et al.
Journal of Clinical Epidemiology|March 2, 2023
Effective quality control in the medical literature: investigation and retraction vs inactionAmanda C de C Williams, Leslie Hearn, R Andrew Moore, et al.
Pain|March 20, 2023
Reply to MonticoneNeil Edward O'Connell, R Andrew Moore, Gavin Stewart, et al.
The Journal of Pain|July 15, 2023
Trials We Cannot Trust: Investigating Their Impact on Systematic Reviews and Clinical Guidelines in Spinal PainNeil O'Connell, R Andrew Moore, Gavin Stewart, et al.
Health Technology Assessment (Winchester, England)|October 5, 2024
Antidepressants for pain management in adults with chronic pain: a network meta-analysisHollie Birkinshaw, Claire Friedrich, Peter Cole, et al.
Pageof 7