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Addressing Common Methodological Flaws in Health Research

Addressing Common Methodological Flaws in Health Research Webinar
October 7, 2026 at 12:00 PM ET

Join Leeds Institute of Science and Technology for an insightful webinar on how to prevent or correct common methodological flaws in health research.

With reproducibility now a major concern in health research, methodological rigor is no longer optional. Most researchers unknowingly repeat the same methodological mistakes. This is one of the reasons for most manuscript rejections.

Understandably, other factors contribute to the acceptance or rejection of a manuscript, but methodological rigor is a requirement that must be fulfilled before acceptance. It is vital in publishing any manuscript in a quality journal.

In this webinar, Dr. Ebenezer Ogunsakin, a biostatistician and research methodologist at Leeds Institute of Science and Technology, will examine common, documented errors observed in health research and equip you with strategies to avoid the errors and their causes. He will share his unique perspectives on what policymakers and reviewers look for, from study design justification to appropriate statistical reporting, giving your manuscripts a very high probability of acceptance. This webinar offers a practical checklist to audit your current or upcoming studies and make your research reproducible and impactful.

Disclaimer: This webinar is a sponsored educational presentation hosted by JMIR Publications in partnership with the Leeds Institute of Science and Technology. The content and opinions expressed are those of the presenter and do not necessarily reflect the official policies or positions of JMIR Publications.

 

Featured Speaker

Ebenezer Ogunsakin

Dr. Ebenezer Ogunsakin

Dr. Ebenezer Ogunsakin is a biostatistician and subject matter expert at Leeds Institute of Science and Technology, Canada, with over 70 peer-reviewed publications. His research develops and applies advanced statistical methods to complex, real-world health data, focusing on modeling disease patterns across space and time, and analyzing time-to-event and repeated-measures outcomes in clinical and public health studies. Ebenezer completed a PhD in statistics at the University of KwaZulu-Natal, South Africa. He is a research associate, School of Data Science and Computational Thinking, Stellenbosch University and adjunct visiting lecturer, School of Health Systems and Public Health, University of Pretoria.


 

Who Should Attend

The session is tailored for early career and experienced researchers, epidemiologists, health policymakers, and health practitioners.


Key Takeaways

  • Prioritize Study Design: Focus on the research framework first, as no amount of analysis can compensate for a flawed study design.

  • Emphasize Proactive Bias Prevention: Implement measures to prevent bias during the study planning phase, which is far more effective than attempting statistical corrections after data collection.

  • Ensure Transparent Reporting: Commit to full and transparent reporting of methods and results to support the replication of findings and advance scientific progress.