This blog is a review of a newly published book, which has the overall aim of giving health professionals a ‘working understanding’ of medical statistics.
This tutorial provides an introduction to statistical averages (mean, median and mode) for beginners to the topic.
A tutorial for understanding and calculating probability. We go back to basics for beginners or for those just wanting a refresher.
The MEDICS initiative aims to ensure a fundamental level of medical statistics and risk communication for medical students. Lathan Liou, founder of MEDICS, invites S4BE students to get involved.
Learn more about the measures of central tendency (mean, mode, median) and how these need to be critically appraised when reading a paper.
Participants in clinical trials may exit the study prior to having their results collated; in this case, what do we do with their results?
A brief guide to prevalence and incidence with definitions, explanations and example calculations.
This blog introduces you to standardised mortality ratios. What are they, why are they used, how do you calculate them and what are their advantages and limitations.
This article explores circadian rhythm, the prevalence of its disruption in modern society, and its affects on cancer.
Explaining basic knowledge of statistics with fun visualization tools and interactive functions.
This blog examines what heterogeneity is, why it matters, how you can identify and measure it and how you can then deal with it.
This blog, written by Leonard Goh, was the winner of Cochrane Malaysia and Penang Medical College’s recent evidence-based medicine blog writing competition. Leonard has written an insightful and informative piece to answer the question: ‘Evidence-based health practice: a fairytale or reality’.
This blog follows on from Ammar’s previous post on meta-analysis, and provides further details on the history, value and implementation of this approach.
This blog provides an introduction to sample size and power; what it is, why it’s important to consider when designing a study, and how to carry out a power calculation.
This blog discusses fundamental issues affecting healthcare research, which could undermine the field and mean that most medical research may be wrong. Issues discussed include: 1) contradictory findings 2) the illusion of high impact factor journals 3) the reproducibility crisis 4) a lack of translation of research findings from bench to bedside 5) medical reversal 6) bias 7) statistical issues and 8) conflicts of interest and unethical practice. The author then explores possible solutions to these.
‘Evidence-based practice’ is a commonly used phrase. But this blog asks the question: ‘just how much can we trust published scientific literature?’ with particular reference to the problems of publication bias and statistical approaches.
This blog explains what is meant by Type I and Type II errors in statistics. Whereby we can end up with false positive and false negative results.
This blog uses 3 examples to demonstrate that, even though there may be an association between two events or variables, this does not mean that one has caused the other.
A nuts and bolts tutorial on how to read a forest plot, featuring a couple of exercises so that you can test your own understanding.
Let’s figure out how to get the essential information from a meta-analysis at a glance, by studying a forest plot.
Median has come to be known for its fair reflection in the case of outliers. However, it is not a perfect statistic. Let me tell you about 3 defects the median as a measure of average.
Come with me. I’ll show you the best way to display the efficacy of a drug. And the pitfalls around it. Ladies and gentlemen, welcome to the world of Number needed to treat.
Confused about Hazard Ratios and their confidence intervals? This blog provides a handy tutorial.
This post talks about the real meaning of p-value. No fancy words. No complicated definitions. Only simple notions included.
How can you tell if a variable is nominal, ordinal, or numerical? Why does it even matter? Determining the appropriate variable type used in a study is essential to determining the correct statistical method to use when obtaining your results. It is important not to take the variables out of context because more often than not, the same variable that can be ordinal can also be numerical, depending on how the data was recorded and analyzed. This post will give you a specific example that may help you better grasp this concept.
Know Your Chances: Understanding Health Statistics is one of the few easily digestible statistics books that teaches anyone the most basic principles and concepts how to question and see the reality behind health news, hype, claims and ads.
As calculating the mean is so popular it might lead to many intuitive misconceptions. Here are some precautions you can take when interpreting the mean.
Terms such as significant, hypothesis testing, and p-value are usually found in research papers, here is a review explaining them.
In search of a book with simple, comprehensible definitions and examples of clinical evidence? Do you want to take the first step in understanding common terms in clinical evidence as well as commonly used methods and their pitfalls? This review will inform you if this is the book you’re looking for.
Is this your first contact with evidence-based healthcare? This course is a perfect start…
What happens when you have a test result? Do you believe it, can you act on it? It all depends where you are. Check out this discussion of post-test probabilities and how they help in the interpretation of test results.
Sean reviews the Statistics Learning Centre’s Videos – a Youtube channel featuring a series of free tutorials which aim to help you learn the concepts of statistics from identifying types of data to performing t-tests in Excel.
Sean reviews ‘What is Evidence Based Medicine and Why Should I care?’, an article for students and healthcare professionals which covers Evidence-Based Medicine from first principles to medical statistics in the course of one free paper.
On the uniform of every fine detective, badges which salute their sensitivity and specificity are worn. From crime to clinic, find out what defines these “pre-test” probabilities.
Pre-test probabilities can help clinicians select and interpret diagnostic tests. To see a recent, real life application check out Aaron’s review of “Diagnostic Accuracy of Point-of-Care Tests for Detecting Albuminuria” from the Annals of Internal Medicine.
Danny has reviewed Testing Treatments Interactive, a website to help you understand more about fair tests and research.
I have a test, and I know its measure of sensitivity. What does this tell me? When should I use this test? How do I expect this test to perform? Read more about the clinical application of sensitivity.
On the uniform of every fine detective, badges which salute their “sensitivity” and “specificity” are worn. From crime to clinic, find out what defines these “pre-test” probabilities.
An introduction to the role of statistical power in the search for evidence.
The nuts and bolts 20 minute tutorial from Tim.
Systematic reviews aren’t cheap or quick – Alice looks at some suggestions from the blogs of Jon Brassey from TRIP and Mona Nasser from Cochrane.
Revealing the truth behind rates, ratios and risk with QMP statistics tutorials. This is one of a series that helps with understanding of statistics and study design.
Understanding uncertainty is a site from the Winton programme based at the University of Cambridge, UK, that encourage healthy criticism of the statistics the media gives us.
QMP Statistics tutorials talks you through chi-squared and t-tests – a useful resource for different statistical levels.
Conducting trials where the trialled therapeutic must be commenced urgently raises specific practical and ethical problems. Here I discuss a recent New England Journal of Medicine paper looking at the use of intracranial pressure monitoring for severe traumatic brain injury as an example of how these issues may affect a trial’s utility and how this can be managed.
David explains risk and number needed to treat using an article from the New England Journal of Medicine
Need something for your EBM task? Check out EBHC wiki!! You will find it there..
Dr Cates provides easy to read re-freshers on statistics and EBM topics
This tutorial teaches the essentials about the statistics in medicine and covers various aspects of normal distribution (ND): central limit theorem, properties of ND, NDs with different means and with different variances, variables that follow a ND, normal plot and introduction to t-distribution
A must-have tutorial on how to critically appraise research.
QMP Medical Statistics Tutorials are a great place to start learning about the principles of evidence-based medicine. The probability & significance test, in my opinion, should be one of the first tutorials for a medical student.
This tutorial teaches you about one of the biggest enemies of strong evidence in clinical research – bias, as well as measurements and outcomes in the clinical trial.
A review of an evaluating risk online course for 11 – 16 year olds, by our youngest blogger Liv!
A short article on the uses of Facebook friend finder…
Beginners often get confused with odds ratio and relative risk, which are almost used in same sense.
A simple way to understand both.
The QMP Medical Statistics tutorial that is designed to show you how to apply evidence-based medicine to clinical practice in a practical and logical manner.
Statistically funny – the blog that combines cartoons, humour, and demystifying evidence-based medicine.
This tutorial covers how to use appropriate statistical tests and what are confidence intervals and how do you use them.
This is a tutorial that looks at the statistical basis of randomised controlled trials, the theory behind meta-analyses and how to read a meta-analysis
This is an information skills tutorial that provides the opportunity for students to learn more about searching for information
A good website from the Centre for Evidence-Based Medicine (CEBM) – with a wide range of tools to help with evidence-based research
The BMJ has on its website a series of articles on how to read papers, including clear explanations of the statistics commonly used and common pitfalls found in studies.
This is a short, clearly written tutorial explaining the basic concepts of evidence-based medicine.
A short poem about regression to the mean illustrated with a few examples!
SPSS is a computer program used for statistical analysis. This tutorial will take you through a series of activities to help improve your SPSS skills.
In this medical statistics tutorial we will be looking at how the data that are collected by studies are summarized and presented in order to extract useful information. We will then start to look at how to analyse the data.
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