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.
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McMaster 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.
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What is meant by intention to treat analysis? Survey of published randomised controlled trials
Results of a survey to document the meaning of ‘intention to treat’ analysis.
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The interpretation of clinical trials
Peter Greenberg’s 9-minute read on the interpretation of clinical trials.
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Assessing Risk of Bias in Included Studies
An introduction to assessing risk of bias using the Cochrane ‘Risk of Bias Tool’.
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University of Western Australia: Bias Minimisation, randomisation and blinding
University of Western Australia’s explanation of why random allocation to comparison groups and blinding (if possible) are important.
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What is a meta-analysis? How to use a systematic review
Oxford University’s Centre for Evidence-Based Intervention guide on how to use evidence from systematic reviews.
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Do the statistics back up the claim?
‘Ask for Evidence’ introduction to the interpretation and assessment of statistics.
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Is the trial valid?
An article from the PEDro database on assessing the validity of a study.
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Goals and tools in Prognosis evaluation
How to assess prognosis in Michigan State University’s Evidence-Based Medicine Course.
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Evaluating the validity of a therapy study
A web-based Duke University tutorial explaining how to address the question: are the results of the study valid?
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‘Tricks to help you get the result you want from your study (S4BE)
Inspired by a chapter in Ben Goldacre’s ‘Bad Science’, medical student Sam Marks shows you how to fiddle research results.
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Strictly Cochrane: a quickstep around research and systematic reviews
An interactive resource explaining how systematic and non-systematic reviews differ, and the importance of keeping reviews up to date.
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Bias – the biggest enemy
University of New South Wales Medical Stats Online Tutorial 5 addresses ‘Bias - the biggest enemy’.
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Appraising the evidence
Six key slides produced by the University of Western Australia to introduce critical appraisal.
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Critical appraisal of clinical trials
Slides developed by Amanda Burls for an interactive presentation covering the most important features of well controlled trials.
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Tips for understanding Intention-to-Treat analysis
Ignoring non-compliance with assigned treatments leads to biased estimates of treatment effects. ITT analysis reduces these biases.
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Defining Bias
This blog explains what is meant by ‘bias’ in research, focusing particularly on attrition bias and detection bias.
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Data Analysis Methods
A discussion of 2 approaches to data analysis in trials - ‘As Treated’, and ‘Intention-to-Treat’ - and some of the pros and cons of each.
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Making sense of randomized trials
A description of how clinical trials are constructed and analysed to ensure they provide fair comparisons of treatments.
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Compliance with protocol and follow-up in clinical trials
Denis Black’s 10-min, downloadable, PowerPoint presentation on compliance, follow up, and intention-to-treat analysis in clinical trials.
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The need to compare like-with-like in treatment comparisons
Allocation bias results when trials fail to ensure that, apart from the treatments being compared, ‘like will be compared with like'.
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Attrition bias, publication bias, comparator bias and commercial bias
6 slides and a 3-min commentary on attrition bias, publication bias, comparator bias and commercial bias (from Univ Mass Med School).
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Randomized Controlled Trial Protocols
A 1-hour videoed lecture explaining protocols for Randomized Control Trials (RCTs).
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Methodology of clinical trials
Eurordis training on the methodology of clinical trials for representatives of patients’ organisations.
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Following up everyone in treatment comparisons
After taking the trouble to assemble comparison groups to ensure that like will be compared with like, it is important […]
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