Abstract
In this paper, I attempt to introduce physical therapists to the most common statistical tests for analysing differences between repeated measurements over time. Using the example of 'whole-body flexibility' recorded at six different times of day and the Statistical Package for the Social Sciences (SPSS), I discuss the advantages and disadvantages of the various approaches for analysing a simple one-factor design. The most important issues in test selection for repeated measures are the exploration of, and correction for, the violation of 'sphericity' when employing a univariate general linear model (GLM), as well as the sample size when adopting a multivariate GLM. I summarize current advice on choice of test with the aid of a 'decision tree', based on the results of documented statistical simulations which have investigated how the various statistical tests 'perform' in certain situations. Lastly, I comment on the most appropriate ways to present and interpret data drawn from serial measurements.
| Original language | English |
|---|---|
| Pages (from-to) | 194-208 |
| Number of pages | 15 |
| Journal | Physical Therapy in Sport |
| Volume | 2 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 1 Jan 2001 |
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