Table 4.
Sample sizes required to detect genetic associations combining different family structures and using only the same family structures for high penetrances* and no measurement errors
| Using both (0, 3, 2) and (0, 3, 1) |
Using only (0, 3, 2) |
Using only (0, 3, 1) |
|
|---|---|---|---|
| Dominant | |||
| p = 0.05 | 338(373) | 208 | 355 |
| p = 0.20 | 185(217) | 187 | 184 |
| p = 0.70 | 1746(2104) | 2539 | 1417 |
| Recessive | |||
| p = 0.05 | 48005(45598) | 17237 | 55431 |
| p = 0.20 | 1139(1126) | 534 | 1275 |
| p = 0.70 | 155(159) | 150 | 152 |
| Multiplic. | |||
| p = 0.05 | 1513(1669) | 1116 | 1556 |
| p = 0.20 | 443(486) | 359 | 459 |
| p = 0.70 | 333(358) | 348 | 322 |
| Additive | |||
| p = 0.05 | 869(967) | 615 | 898 |
| p = 0.20 | 335(376) | 299 | 342 |
| p = 0.70 | 485(534) | 534 | 459 |
*
The values in brackets are based on the weighting scheme suggested by Risch & Teng (1998); Significance level α = 5 × 10−8; power 1 − β = 0.80; Dominant model: f2 = f1 = 0.4, f0 = 0.1; Recessive model: f2 = 0.4, f1 = f0 = 0.1; Multiplicative model: f2 = 0.4, f1 = 0.2, f0 = 0.1; Additive model: f2 = 0.4, f1 = 0.25, f0 = 0.1.