Regression estimates for part-worth utility*
| Attribute and level | Part-worth utility, mean† | Part-worth utility, SD‡ | Part-worth utility < 0, %§ |
|---|---|---|---|
| Risk of disease, % lifetime risk | |||
| ≥ 5 | −0.85¶ | 0.37¶ | 99 |
| ≥ 40 | Reference | — | — |
| ≥ 80 | 0.48¶ | 0.02 | 0 |
| ≥ 90 | 0.52¶ | 0.11 | 0 |
| Disease treatability | |||
| No treatment recommended | −0.59¶ | 0.05 | 100 |
| Recommended effective lifestyle change only | Reference | — | — |
| Recommended effective medical treatment only | 0.11¶ | 0.26¶ | 34 |
| Recommended effective medical treatment and lifestyle change | 0.42¶ | 0.42¶ | 16 |
| Disease severity (health consequences) | |||
| Mild | −0.20¶ | 0.18 | 0 |
| Moderate | 0.002 | 0.08 | 0 |
| Severe | 0.11¶ | 0.05 | 0 |
| Very severe | Reference | — | — |
| Carrier status | |||
| Yes | 0.11¶ | 0.51¶ | 42 |
| No | Reference | — | — |
| Cost to you | −0.0016¶ | — | — |
Note: SD = standard deviation.
↵* Pseudo R2 for this model = 0.57.
↵† The mean part-worth utility value indicates the utility associated with each attribute level. Part-worth utility values can be summed to indicate the overall utility of a good. For example, returning incidental findings of a disease with a 90% lifetime risk of occurrence or higher, with medical treatment available and with severe health consequences, has an overall utility of 0.74.
↵‡ The SD is an estimated model parameter (with its own standard error indicating statistical significance) that is used to estimate the dispersion of individual-level utility values in the population. Using the mean and SD, individual-level estimates of personal utility can be determined, including determination of the percentage of estimates expected to fall below zero.
↵§ The percentage of the population with negative part-worth utility values.
↵¶ p < 0.05.