Table 2.
Summary of GLME models predicting probability of reporting harm within each domain as a function of time (gamblers only)
|
Link function: Binomial (logit)
Dependent variable: p(harm) |
||||||
| Financial | Relat. | Emotional/Psych. | Health | Work/Stud. | Other | |
| Fixed effects B (SE) | ||||||
| log (time +1) | −0.862* | −0.962* | −0.969* | −0.779* | −0.797 | −0.839* |
| (0.092) | (0.149) | (0.126) | (0.167) | (0.342) | (0.323) | |
| Constant | −2.953* | −3.966* | −2.882* | −5.544* | −9.046* | −8.535* |
| (0.356) | (0.306) | (0.255) | (0.700) | (0.716) | (0.650) | |
| Random effects SD | ||||||
| Response IDa | 1.584 | 2.481 | 2.189 | 3.222 | 6.246 | 5.790 |
| Harm IDb | 1.302 | 0.305 | 0.514 | 0.537 | 0.739 | 0.565 |
| Observations | 10,448 | 8,489 | 7,183 | 10,448 | 7,836 | 10,448 |
| Log Likelihood | −2,128.14 | −1,305.03 | −1,603.56 | −1,318.07 | −533.36 | −658.40 |
| Akaike Inf. Crit. | 4,264.28 | 2,618.07 | 3,215.13 | 2,644.13 | 1,074.72 | 1,324.80 |
| Bayes. Inf. Crit. | 4,293.29 | 2,646.25 | 3,242.64 | 2,673.15 | 1,102.58 | 1,353.81 |
Note: *P < 0.01, a The standard deviation of random intercepts across individuals, b The standard deviation of random intercepts across specific harms within each domain.