Table 1 The relationship between the proportion of measures and subjects versus intra-class correlation relative to the proportion needed when only one measure is employed (top rows). The lower table shows the effective percentage increase in study efficiency (in terms of subjects) that can be achieved by taking multiple samples. For example, a two-sample study with an ICC of 0.5 is equivalent to a one-sample study with 33% more subjects (as is also apparent from the first table in the 75 to 100 difference)
From: Employing multiple synchronous outcome samples per subject to improve study efficiency
%Measures/% Subjects | ||||||||
|---|---|---|---|---|---|---|---|---|
Intra-Class Correlation | ||||||||
Measures | 0 | 0.15 | 0.35 | 0.5 | 0.65 | 0.85 | 0.9 | 1 |
1 | 100 / 100 | 100 / 100 | 100 / 100 | 100 / 100 | 100 / 100 | 100 / 100 | 100 / 100 | 100 / 100 |
2 | 100 / 50 | 116 / 58 | 136 / 68 | 150 / 75 | 166 / 83 | 186 / 93 | 190 / 95 | 200 / 100 |
3 | 99 / 33 | 129 / 43 | 171 / 57 | 201 / 67 | 231 / 77 | 270 / 90 | 279 / 93 | 300 / 100 |
4 | 100 / 25 | 144 / 36 | 204 / 51 | 252 / 63 | 296 / 74 | 356 / 89 | 372 / 93 | 400 / 100 |
5 | 100 / 20 | 160 / 32 | 240 / 48 | 300 / 60 | 360 / 72 | 440 / 88 | 460 / 92 | 500 / 100 |
Effective Sample Size | ||||||||
Measures | ||||||||
1 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 |
2 | 200 | 174 | 148 | 133 | 121 | 108 | 105 | 100 |
3 | 300 | 231 | 176 | 150 | 130 | 111 | 107 | 100 |
4 | 400 | 276 | 195 | 160 | 136 | 113 | 108 | 100 |
5 | 500 | 313 | 208 | 167 | 139 | 114 | 109 | 100 |