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.
This blog is a critical appraisal of a randomised controlled trial looking at the effects of additional therapy on young children with spastic cerebral palsy.
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 of it.
Let’s find out why physicians sometimes contradict each other from a statistical perspective. And see how students can learn from that.
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.
A description of the two types of data analysis – “As Treated” and “Intention to Treat” – using a hypothetical trial as an example
This blog describes what is meant by a positive predictive value and a negative predictive value, their purpose and how they can be interpreted
Sense About Science explains how scientists cope with uncertainty and unknowns in research, whether or not that matters, and how we can practically use scientific results in spite of not always knowing everything.
In his new book, Dr. Goldacre continues his crusade of exposing quacks and pseudoscience, with an emphasis on how journalists totally mislead the public about what a scientific paper really says. He also chronicles his AllTrials quest by railing against the lack of transparency in clinical trials and publication bias.