Optimum Sample Size to Detect Perturbation Effects: The ...

Table 1. Power values (probabilities) for an ANOVA design with a = 0.05. For 2 to 25 N° of treatments and for each one of the habitats analysed by Mouillot et al. (1999).
A small effect size is 0.1, medium effect is 0.25 and a large effect is 0.4 (sensu Cohen, 1988).
power (with Type I error = 0.05)
N°
marine habitats
treatment - 1
seagrass west rocky bottoms south rocky bottoms east
(k-1)
variability coefficient variability coefficient variability coefficient
10 % 25 % 10 % 25 % 10 % 25 %
(comparisons) sample size sample size sample size
n = 118 n = 19 n = 112 n = 18 n = 130 n = 21
effect size effect size effect size
0.1 0.25 0.4 0.1 0.25 0.4 0.1 0.25 0.4 0.1 0.25 0.4 0.1 0.25 0.4 0.1 0.25 0.4
1 34 97 99 9 33 68 29 94 99 8 31 66 36 98 99 9 36 73
2 38 99 99 9 36 76 32 98 99 9 34 73 41 99 99 9 40 80
3 43 99 99 9 41 83 36 99 99 9 39 80 46 99 99 10 45 87
4 47 99 99 10 45 88 40 99 99 9 43 86 50 99 99 10 50 91
5 52 99 99 10 49 92 44 99 99 10 47 90 55 99 99 11 54 94
6 56 99 99 11 53 94 47 99 99 10 51 93 60 99 99 11 58 96
8 63 99 99 11 60 97 54 99 99 11 57 97 67 99 99 12 66 99
10 69 99 99 12 67 99 60 99 99 12 64 98 73 99 99 13 72 99
12 74 99 99 13 72 99 65 99 99 12 69 99 78 99 99 14 77 99
15 81 99 99 14 78 99 71 99 99 13 76 99 83 99 99 15 84 99
24 92 99 99 21 97 99 85 99 99 16 89 99 94 99 99 18 94 99
Note: n = average sample size and coefficient of variability per habitat from Mouillot et al. (1999)
4 Ortiz