Repeated Measures Design Tests

Repeated measures design tests each patient: either for different conditions or for the same condition overtime (at different time points). For example, comparing the effect of medications to exercise in obese patients or, serially testing the effect of either condition overtime; all being carried out in the same group of patients.

As each patient serves as his own control, the design significantly reduces sample size, cuts out the noise of individual variability, eliminates confounders and increases study sensitivity to detect a statistically significant effect size.

Workshop items:

• Design advantages and disadvantages

• Ordinary versus crossover designs

• Randomization and counterbalancing

• Sample size calculation

• Popular statistical tests:

  • Repeated measures ANOVA

  • Friedman’s test

  • Cochran Q test

  • McNemar’s test

• Application on SPSS