Table 1.
Power to determine the number of studies needed to show a moderator effect in a given meta-analysis dataset
Proportion of studies (%) with positive expression of moderator (for example, ‘high quality’) | ||||
---|---|---|---|---|
Studies (
n
) |
0.5 |
0.3 |
0.2 |
0.1 |
Moderator effect = 0 | ||||
200 |
6 |
6 |
5 |
6 |
400 |
6 |
5 |
6 |
5 |
600 |
5 |
6 |
6 |
6 |
800 |
6 |
5 |
6 |
7 |
Moderator effect = 0.1 | ||||
200 |
24 |
22 |
22 |
13 |
400 |
45 |
40 |
33 |
21 |
600 |
65 |
54 |
48 |
29 |
800 |
75 |
69 |
53 |
39 |
Moderator effect = 0.2 | ||||
200 |
75 |
67 |
57 |
32 |
400 |
95 |
93 |
84 |
60 |
600 |
100 |
99 |
96 |
78 |
800 | 100 | 100 | 98 | 90 |
Extrapolated from random sample of 200 RCTs, I2 = 92%, τ2 = 0.285; mean sample size 132; alpha = 0.05; in the absence of a moderator effect (moderator effect = 0), the power should vary around 5%.