M
Matthew J. Page
Researcher at Monash University
Publications - 165
Citations - 48068
Matthew J. Page is an academic researcher from Monash University. The author has contributed to research in topics: Systematic review & Medicine. The author has an hindex of 43, co-authored 128 publications receiving 12149 citations. Previous affiliations of Matthew J. Page include University of Bristol & Monash University, Clayton campus.
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An empirical investigation of the potential impact of selective inclusion of results in systematic reviews of interventions: study protocol
TL;DR: The association between selection of trial outcome data included in a meta-analysis and the magnitude and statistical significance of the trial result will be investigated and the impact of the selected trial result on the magnitude of the resulting meta-analytic effect estimates is investigated.
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Controversy and Debate on Meta-epidemiology. Paper 4: Confounding and other concerns in meta-epidemiological studies of bias.
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Reporting of allocation method and statistical analyses that deal with bilaterally affected wrists in clinical trials for carpal tunnel syndrome.
TL;DR: There was no clear trend of improved reporting over time in clinical trials for carpal tunnel syndrome and interventions are needed to improve reporting quality and statistical analyses of these trials so that these can provide more reliable evidence to inform clinical practice.
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Ensuring Prevention Science Research is Synthesis-Ready for Immediate and Lasting Scientific Impact
Emily A. Hennessy,Rebecca L. Acabchuk,Pieter A. Arnold,Adam G. Dunn,Yong Zhi Foo,Blair T. Johnson,Sonya R. Geange,Sonya R. Geange,Neal R. Haddaway,Shinichi Nakagawa,Witness Mapanga,Kerrie Mengersen,Matthew J. Page,Alfredo Sánchez-Tójar,Vivian Welch,Luke A McGuinness +15 more
TL;DR: In this paper, the authors provide a set of practical guidelines to help prevention scientists prepare synthesis-ready research, and highlight several tools and practices that can aid authors in these efforts, such as using a data-driven approach for crafting titles, abstracts, and keywords or creating a repository for each project to host all study-related data files.
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Rates and predictors of data and code sharing in the medical and health sciences: Protocol for a systematic review and individual participant data meta-analysis.
Daniel G. Hamilton,Hannah Fraser,Fiona Fidler,Steve McDonald,Anisa Rowhani-Farid,Kyungwan Hong,Matthew J. Page +6 more
TL;DR: This systematic review aims to synthesise the findings of medical and health science studies that have empirically investigated the prevalence of data or code sharing, or both, to provide some insight into how often research data and code are shared publicly and privately, how this has changed over time, and how effective some measures such as the institution of data sharing policies and data availability statements have been in motivating researchers to share their underlying data andcode.