2-17 Don’t confuse “statistical significance” with “importance”

Know Your Chances

This book has been shown in two randomized trials to improve peoples' understanding of risk in the context of health care choices.

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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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Basic statistics for clinicians: 1. Hypothesis testing

The statistical concepts of hypothesis testing and p values.

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Basic statistics for clinicians: 2. Interpreting study results: confidence intervals

Interpreting study results: confidence intervals.

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Basic statistics for clinicians: 3. Assessing the effects of treatment: measures of association

Assessing the effects of treatment: measures of association.

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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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Critical Appraisal of Research Evidence 101

Ontario Public Health Libraries Association guide to critical appraisal of research evidence.

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Understanding Health Research, a tool for making sense of health studies: use of statistics

In health research, researchers typically use statistics to determine statistical significance and effect size.

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Understanding Health Research: A tool for making sense of health studies

An interactive online tool designed to help anybody to understand scientific health research evidence.

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Reading the Medical literature

American College of Obstetricians and Gynaecologists (ACOG) introduction to critical appraisal and evidence-based medicine.

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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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Evaluating relevance

How to evaluate relevance of research in Michigan State University’s Evidence-Based Medicine Course.

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Evidence-Based and Shared-Informed Decision-Making According to Homer (Simpson)

With help from Homer Simpson, James McCormack uses a 17-minute slide cast to explain the principles of thoughtful treatment.

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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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The Princess and the p-value

An interactive resource introducing reporting and interpretation of statistics in controlled trials.

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Sampling error, the unspoken issue behind small number changes in the news

Ben Goldacre stresses the importance of taking account of “sampling variability” and confidence intervals.

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Critical appraisal

University of New South Wales Medical Statistics Tutorial 4 addresses Critical Appraisal.

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Probability and tests of statistical significance

University of New South Wales Medical Statistics Tutorial 6 addresses ‘Probability and tests of statistical significance’.

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Quantifying uncertainty in treatment comparisons

Small studies in which few outcome events occur are usually not informative and the results are sometimes seriously misleading.

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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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GenerationR – The importance of involving children and young people in research

3/3, 22-min video at the launch of GenerationR, a network of young people who advise researchers.

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Clinical Significance – CASP

To understand results of a trial it is important to understand the question it was asking.

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Making sense of results – CASP

This module introduces the key concepts required to make sense of statistical information presented in research papers.

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Significant Others

Statistical significance does not always mean meaningful or practical significance.

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False Precision

The use of p-values to indicate the probability of something occurring by chance may be misleading.

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Personal “No Worse”

People with vested interests may use misleading statistics to support claims about the effects of new treatments.

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P-values and the role of chance

Gilbert Welch’s 10-min video on p-values and assessing the likelihood that a difference between treatments is due to chance.

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Mixed Messages about Statistical Significance

A webpage explaining the difference between statistical and practical significance.

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Statistical Significance and Practical Significance

Keith Bower’s 3-min video discussing the difference between Statistical Significance and Practical Significance.

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Type I and Type II errors, and how statistical tests can be misleading

Gilbert Welch’s 12-min video explaining Type I and Type II errors, and how statistical tests can be misleading.

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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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Reporting results of studies

Dr Chris Cates' article discussing how to report study results, with emphasis on P-values and confidence intervals.

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3: Statistics are confusing – should patients really have to look at the numbers?

The way that numbers are presented can be very daunting – or even downright misleading. But if you really do […]

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What does “statistically significant” mean?

‘To be honest, it’s a tricky idea. It can tell us if the difference between a drug and a placebo […]

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What does a “significant difference” between treatments mean?

Well, this is a trick question, because ‘significant difference’ can have several meanings. First, it can mean a difference that […]

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