Table 4.
A Multivariate Analysis of Exposures That Could Contribute to Prostate Hyperplasia Outcomes in Offspring.
| Multivariate GLMa of Offspring Prostate Hyperplasia | ||||
|---|---|---|---|---|
| Estimated Effect Size | Std Error | t Value | Pr(>|t|) | |
| (Intercept) | −0.3012 | 1.2642 | −0.2383 | 0.8117 |
| Maternal diet | 0.8261 | 0.2261 | 3.6542 | 0.0003 |
| Age cohort | 1.2585 | 0.3292 | 3.8233 | 0.0001 |
| Days old when analyzed | −0.0039 | 0.0015 | −2.6206 | 0.0094 |
| Body weight | −0.0202 | 0.0336 | −0.6007 | 0.5513 |
| Cage density | 0.2844 | 0.1380 | 2.0609 | 0.0394 |
| Log (maternal exposure length) | 0.0957 | 0.2631 | 0.3636 | 0.7162 |
Abbreviation: AIC, Akaike information criterion; GLM, generalized linear model; SE, standard error.
aNull deviance: 106.662 on 52 degrees of freedom; residual deviance: 76.369 on 46 degrees of freedom; AIC: 200.4. Estimated effect size = b. t value = b/SE(b).