For each structural parameter, click the buttons below Style multiple times to toggle through the different style options.
Product*exp(Eta)
Sum*exp(Eta)
exp(Sum+Eta)
ilogit(Sum+Eta)
Sum+Eta
In the Fixed Effect field, type a name for the fixed effect.
The default is tv (typical value) + parameter name (e.g., tvV, tvKe, etc.).
Check the box beside each parameter to add a random effect to the structural parameter.
The parameter is added to the Random Effects tab.
In the Random Effect field, type a name for the random effect.
The default n (eta) + parameter name (e.g., nKa, nV, nKe, etc.).
Note: Removing a random effect from the Structural Parameters tab that is used in random effects will reset the matrices on the Random Effects tab. The matrices, therefore, will need to be redefined.
The most common recommended form is Product*exp(eta) for positive-only parameters like V, CI, or various Ks. For parameters like E0 or Emax, which can be positive or negative, Sum+eta is the preferred choice. For parameters that are constrained to fall between zero and one, ilogit(Sum+eta) is a useful choice.
If there are no covariates, Product*exp(eta) and Sum*exp(eta) yield nearly identical expressions in the model code. The differences between the two are seen when there are covariates and they come into the equation either through multiplication or addition. For example, here is what Product*exp(eta) provides in the presence of covariate effects, where V and Cl on Gender, wgt, and apgr have been chosen:
stparam(V=tvV
*(wgt/mean(wgt))^dVdwgt
*(apgr/median(apgr))^dVdapgr
*exp(dVdGender1*(Gender==1))
*exp(dVdGender2*(Gender==2))
*exp(nV)
)
stparam(Cl=tvCl
*(wgt/mean(wgt))^dCldwgt
*(apgr/median(apgr))^dCldapgr
*exp(dCldGender1*(Gender==1))
*exp(dCldGender2*(Gender==2))
*exp(nCl)
)
Here is what Sum*exp(eta) gives you in the presence of covariate effects:
stparm(V-(tvV
+(wgt-mean(wgt))*dVdwgt
+(apgr-median(apgr))*dVdapgr
+(Gender==1)*dVdGender1
+(Gender==2)*dVdGender2
)
*exp(nV))
stparm(Cl=(tvCl
+(wgt-mean(wgt))*dCldwgt
+(apgr-median(apgr))*dCldapgr
+(Gender==1)*dCldGender1
+(Gender==2)*dCldGender2
)
*exp(nCl))