Statistical modeling methods have had increasing use in drug disposition studies, both to estimate pharmacokinetic parameters and to develop regression models that relate these parameter estimates to patient characteristics. These methods are particularly flexible as they allow non-linearity and sparse within-patient information. In the past few years, multiple analysis methods have become available, but there is a lack of systematic comparisons of their estimates on the same data sets. Two simulated data sets were therefore developed by the Population Modeling Workgroup of the Biopharmaceutical Section of the American Statistical Association. We analysed these data sets using seven population modeling programs, some of which contain multiple analysis methods. Although each data set represents a single replicate from a given model and data collection design, the results suggest that the behaviour of some methods differs from that of the others.
|Original language||English (US)|
|Number of pages||22|
|Journal||Statistics in Medicine|
|State||Published - Jun 15 1997|
ASJC Scopus subject areas
- Statistics and Probability