Summary of principal covariate models tested in population analysis (one compartment structure)
| Model number | Covariate model | ΔOFV |
Comparison model | |||||
| 1 | Basic model | 0.0 | ||||||
| 2 | Does weight influence CL | 77.8 | 1 | Yes | ||||
| (CL = θ1 × weight, V = θ2) | ||||||||
| 3 | Is an intercept required? | 0.0 | 2 | No | ||||
| (CL = θ1 + θ2 × weight, V = θ3) | ||||||||
| 4 | Does PCA influence CL? | 98.0 | 1 | Yes | ||||
| (CL = θ1 × PCAθ2, V = θ3) | ||||||||
| 5 | Does creatinine concentration influence CL? | 100.1 | 1 | Yes | ||||
| (CL = θ1 × creatinineθ2, V = θ3) | ||||||||
| 6 | Can 1/creatinine be substituted for creatinineθ2? | −4.9 | 5 | Yes | ||||
| (CL = θ1 / creatinine, V = θ2) | ||||||||
| 7 | Does adding weight to CL improve model 6? | 57.3 | 6 | Yes | ||||
| (CL = θ1 × weight / creatinine, V = θ2) | ||||||||
| 8 | Does adding PCA improve model 7? | 0.0 | 7 | No | ||||
| (CL = θ1 × weight / creatinine × PCAθ2, V = θ3) | ||||||||
| 9 | Does weight influence V? | 73.5 | 7 | Yes | ||||
| (CL = θ1 × weight / creatinine, V = θ2 × weight) | ||||||||
| 10 | Does adding IV nutrition improve model 9? | 8.2 | 9 | Yes3-150 | ||||
| (CL = θ1 × weight / creatinine × (1 + θ2(NT)), V = θ3 × weight) | ||||||||
| 11 | Does adding gestational age <35 weeks improve model 9? | 7.9 | 9 | Yes3-150 | ||||
| (CL = θ1 × weight / creatinine × (1 + θ2 (GA)), V = θ3 × weight) | ||||||||
ΔOFV = difference in objective function value (>7.9 is significant at p<0.005 for the addition of 1 parameter); θ1...5 = parameter to be estimated; V = volume of distribution; CL = clearance; PCA = postconceptual age; NT = 1 if patient given IV nutrition or 0 otherwise; GA = 1 if gestational age is less than 35 weeks or 0 otherwise;
↵3-150 Borderline significance, omitted from the final model.