Discuss the below:
One of the primary advantages of a repeated-measures design, compared to an independent-measures design, is that it reduces the overall variability by removing variance caused by individual differences. The following data are from a research study comparing three treatment conditions.
1. Assume that the data are form an independent-measures study using three separate samples, each with n = 6 participants. Ignore the column of P totals and use an independent-measures ANOVA with α = .05 to test the significance of the mean differences.
2. Now assume that the data are from a repeated-measures study using the same sample of n = 6 participants in all three treatment conditions. Use a repeated-measures ANOVA with α = .05 to test the significance of the mean differences.
3. Explain why the two analyses lead to different conclusions.
|
Treatment
1
|
Treatment
2
|
Treatment
3
|
P
|
|
|
6
|
9
|
12
|
27
|
|
|
8
|
8
|
8
|
24
|
N = 18
|
|
5
|
7
|
9
|
21
|
G = 108
|
|
0
|
4
|
8
|
12
|
ΣX2 = 800
|
|
2
|
3
|
4
|
9
|
|
|
3
|
5
|
7
|
15
|
|
M = 4 M = 6 M = 8
T = 24 T = 36 T = 48
SS = 42 SS = 28 SS = 34