In this paper, three mathematical cell-kill models including log-kill hypothesis, Norton Simon hypothesis and Emax hypothesis are considered.
The final MP and PP models included log creatinine, income, and the interaction terms sex × race/ethnicity (only for PP), sex × age (p < 0.01), and age × race/ethnicity (p < 0.01) (Table 5).
Continuous models included log-linear, power, linear, and linear-exponential models.
A practical propagation model including log-normal shadow fading is considered in the derivation of the PDF.
However, the AIC comparisons indicated the model including log-age and annual increment provided a better fit to the data than the equivalent model with distance from the pith.
Whereas the second model included log N as a factor (Model 2 in Table 1), the third model included log (N + 1) (Model 3 in Table 1).
bMultivariate model includes log SNP RR, age, BMI, race/ethnicity, age at menarche, age of first birth, family history of breast cancer, breast biopsy and atypical hyperplasia.
The multivariate logistic regression model included log-transformed SNP panel RR, all Gail risk factors (age, race/ethnicity, age at menarche, age at first live birth, first-degree family history of breast cancer, breast biopsy, atypical hyperplasia) and BMI.
The best models were those including SCI index and IUCN score (w = 0.25), and the model also including (log) body mass (w = 0.18).
