What about continuous data?

Some trials don’t measure effect in terms of “did it happen or not”, so called dichotomous data. Instead they measure the effect on a continuous measure such as blood pressure, or months of survival. Confidence Intervals can also be calculated for these measures, and used to assess significance of the result.

Consider a trial comparing the effect of drug X and placebo on FEV1 in patients with chronic obstructive airways disease. At the end of the trial, the FEV1 of patients who received drug X has, on average, declined 50mL less than in those who received placebo. The 95% confidence interval is 5mL - 100mL.

Watch the video first, then answer the question below.

Is this result statistically and clinically significant? Select “yes” or “no”.