One of the major advantages of a repeated-measures desing is that it removes individulal differences from the variance and therefore reduces the standard error. The follwing two sets of data demonstrate this fact. The 1st set of data represents the original results from a repeated measures study. To create the 2nd set of data we started with the original scores but increased the individual differences by adding 10points to each score for subject B, adding 20 points to each score for subject C and adding 30 points to each score for subject D. Note that this change produces a huge increase in the difference from one subject to another and a huge increase in the variability of the scores within each treatment condition
Set 1. Set 2.
Subject I II Subject I II
A 12 14 A 12 14
B 7 17 B 17 27
C 11 12 C 31 33
D 10 12 D 40 42
M=10 M=14 M=25 M=29
SS14 SS=14 SS=494 SS=414
a. Find the difference scored for each set of data and compute the mean and variance for each sample of difference scores.
b. You should find that both sets of data produce the same mean difference and the same variance for the difference scores. Explain what happend to the huge individual difference that were added to the second set of data.