Variations in models using Propofol data
The data in propofol.dat follows a three compartment pharmacokinetic model with IV infusion input. This example uses a model similar to the compiled Least-Squares Regression PK model number 19.
Note: The completed project (Propofol.phxproj) is available for reference in …\Examples\NLME.
Set up the Maximum Likelihood Models object
Create a new project called Propofol.
Import the dataset …\Examples\NLME\Supporting files\propofol.dat.
Press Finish in the File Import Wizard.
Right-click the propofol worksheet in the Data folder and select Send To > Modeling > Maximum Likelihood Models.
In the Structure tab of the ML Model object, select Macro1 from the Parameterization menu.
In the Num Terms menu, select 3.
Check the Infusions possible? box.
From the Residual Error model menu, select Multiplicative.
Type 0.3 in the Stdev field.
Select the Parameters > Fixed Effects sub-tab.
In the Initial column, enter the following initial estimates for each of the study parameters:
tvV = 11
tvAlpha = 0.38
tvB = 0.07
tvBeta = 0.03
tvC = 0.004
tvGamma = 0.002
Select the Random Effects sub-tab.
Type 0.1 in the Initial Estimates fields for nV, nAlpha, nB, nBeta, nC, and nGamma.
Select the Run Options tab.
From the Algorithm menu, select Naive pooled.
Map the model variables
1. In the Main Mappings panel, map the columns to the contexts as follows:
TID to ID.
ID to None. ID cannot be mapped to the ID context.
TIME to Time.
DV to C1Obs.
RATE to A Rate.
AMT to A.
All other data types mapped to None.
2. Click 
(Execute icon) to execute the object.
Accept the new initial estimates
1. Select the Parameter > Fixed Effects sub-tab.
2. Press Accept All Fixed+Random to copy the new estimates to the Initial estimates field for each parameter.
3. Select the Run Options tab.
4. From the Algorithm menu, select FOCE ELS.
5. Execute the object.
Save and close the project
1. Select File > Save Project.
2. Press Save.
3. Select File > Close Project.
The project is saved and closed and Phoenix can be safely exited.
This concludes the model variations using propofol data example.