McMaster Evidence-Based Clinical Practice Workshop Resources – Therapy module
This is the therapy module resources provided to the attendees at the McMaster Evidence-Based Clinical Practice Workshop.
| 0 CommentsMcMaster Evidence-Based Clinical Practice Workshop Resources – Systematic review module
The Systematic review module resources provided to the attendees at the McMaster Evidence-Based Clinical Practice Workshop.
| 0 CommentsMeta-analysis, collaborative overview, systematic review: what does it all mean?
Mike Clarke’s 9-minute read on meta-analysis, collaborative overview, systematic review.
| 0 CommentsThe interpretation of clinical trials
Peter Greenberg’s 9-minute read on the interpretation of clinical trials.
| 0 CommentsCalling Bullshit Syllabus
Carl Bergstrom's and Jevin West's nice syllabus for 'Calling Bullshit'.
| 0 CommentsTom Hanks and Type 2 Diabetes
A 50-minute illustrated talk by James McCormack prompted by Tom Hanks’ announcement that he had been diagnosed with Type 2 diabetes.
| 0 CommentsIt’s just a phase
A resource explaining the differences between different trial phases.
| 0 CommentsBuilding evidence into education
Ben Goldacre explains why appropriate infrastructure is need to do clinical trials of sufficient rigour and size to yield reliable results.
| 0 CommentsApplying the results of trials and systematic reviews to individual patients
Paul Glasziou uses 28 slides to address ‘Applying the results of trials and systematic reviews to individual patients’.
| 0 CommentsThe Mean: Simply Average?
This blog explains ‘the mean’ as a measure of average; describes how to calculate it; and flags up some caveats.
| 0 CommentsUnderstanding Confidence Intervals
A 4-min video explaining the concept of confidence intervals and how they are calculated, with helpful diagrams and examples.
| 0 CommentsMeans vs. Medians
Keith Bower’s 3-min video explaining how means (averages) and medians can be presented misleadingly.
| 0 CommentsMore than average confusion about what mean means mean
Cartoon and blog about how averages can hide important variations in effects.
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GET-IT provides plain language definitions of health research terms