This is the twenty-ninth blog in a series of 36 blogs explaining 36 key concepts we need to be able to understand to think critically about treatment claims.
“Statistical significance” is often confused with “importance”. The cut-off for considering a result as statistically significant is arbitrary, and statistically non-significant results can be either informative or inconclusive.
This is the twenty-eighth blog in a series of 36 blogs explaining 36 key concepts we need to be able to understand to think critically about treatment claims.
The confidence interval is the range within which the ‘true difference’ is likely to lie, after taking into account the play of chance. Whenever possible, consider confidence intervals when assessing estimates of treatment effects. Do not be misled by p-values.
This is the fourteenth blog in a series of 34 blogs explaining 34 key concepts we need to be able to understand to think critically about treatment claims.
This blog explains that if people in the treatment comparison groups differ in ways other than the treatments being compared, the apparent effects of the treatments might reflect those differences rather than actual treatment effects. A method such as allocating people to different treatments by assigning them random numbers (the equivalent of flipping a coin) is the best way to ensure that the groups being compared are similar in terms of both measured and unmeasured characteristics.
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Another 20 minute tutorial from Tim.
The nuts and bolts 20 minute tutorial from Tim.
This new webpage from Cochrane UK is aimed at students of all ages. What is evidence-based practice? What is ‘best available research evidence’? Which resources will help you understand evidence and evidence-based practice, and search for evidence?