Abstract
Two approaches are presented to incorporate covariate effects into dose- response models. The first approach postulates a parametric form for the dose-response function with the resulting parameters then assumed to depend on the covariates. The second approach is semi-parametric: it assumes that the logit ratio (the difference between the logit of success rate at the covariate level and that of the baseline level) can be expressed as a regression model in the covariate effects and the dose level. We present results of a simulation study which compares the efficiency of the two approaches.
Original language | English (US) |
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Pages (from-to) | 977-987 |
Number of pages | 11 |
Journal | Biometrics |
Volume | 51 |
Issue number | 3 |
DOIs | |
State | Published - 1995 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- General Biochemistry, Genetics and Molecular Biology
- General Immunology and Microbiology
- General Agricultural and Biological Sciences
- Applied Mathematics