Table 2.

Effect of covariate analysis on variance of clearance (ω²) – impact of each covariate analysis when added sequentially to the model

Individual covariate alone	PPVt2	BSVR2	BOV2	PPVP2	PPVP2/PPVt2	OBJ
No covariates	0.279	0.279	0	0	0	2835.261
Allometric scaling	0.279*	0.0538	0.0862	0.139	0.498	2632.123
Age
PMA linear	0.279*	0.0449	0.0443	0.190	0.680	2515.136
exponential	0.279*	0.0443	0.0456	0.189	0.678	2519.390
first order	0.279*	0.0446	0.0450	0.189	0.679	2515.461
variable slope sigmoidal	0.279*	0.0452	0.0450	0.189	0.677	2514.865
PNA linear	0.279*	0.0734	0.0373	0.1683	0.603226	2579.162
Renal function	0.279*	0.0362	0.0137	0.230	0.821	2418.198
Ventilation scaling factor	0.279*	0.0356	0.0137	0.230	0.823	2413.725

^*Assumed from no covariate model estimate. PPVt², Total population parameter variability estimated without covariate analysis; BSVP², between-subject variability predictable from covariates, BSVR², random BSV² estimated on a parameter when covariate analysis is included; BOV², between-occasion variability (PPVt² = BSVP² + BSVR² + BOV²). The ratio of the population parameter variability predictable from covariates (PPVP²) to the total population parameter variability obtained without covariate analysis (PPVt²) (i.e. PPVP²/ PPVt²) indicates the fraction of the total variability in the parameter that is predictable from covariates. OBJ, Objective function value measuring the goodness of fit.