Nonparametric population modeling and Bayesian analysis.

Tatiana Tatarinova; Roger Jelliffe; Michael Neely; Alan Schumitzky; David Bayard; Michael Van Guilder; Andreas Botnen; Aida Bustad; Derek Laing; Walter Yamada; Jay Bartroff

doi:10.1016/j.phrs.2011.04.008

Nonparametric population modeling and Bayesian analysis.

Tatiana Tatarinova, Roger Jelliffe, Michael Neely, Alan Schumitzky, David Bayard, Michael Van Guilder, Andreas Botnen, Aida Bustad, Derek Laing, Walter Yamada, Jay Bartroff

Faculty of Computing, Engineering and Science

Research output: Contribution to journal › Article › peer-review

Abstract

The nonparametric (NP) population modeling approach estimated the model parameter values and predicted the observed mycophenolic acid concentrations more precisely than the parametric method did. We expect this because the NP method makes no assumptions about the shape of the model parameter distributions, as parametric methods do, and therefore obtains results that are more likely given the data.

Original language	English
Journal	Pharmacological Research
Volume	64
Issue number	4
DOIs	https://doi.org/10.1016/j.phrs.2011.04.008
Publication status	E-pub ahead of print - 23 Apr 2011

Keywords

pharmacokinetics

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10.1016/j.phrs.2011.04.008

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@article{f81c1eed56074b9a97609ffb3336282f,

title = "Nonparametric population modeling and Bayesian analysis.",

abstract = "The nonparametric (NP) population modeling approach estimated the model parameter values and predicted the observed mycophenolic acid concentrations more precisely than the parametric method did. We expect this because the NP method makes no assumptions about the shape of the model parameter distributions, as parametric methods do, and therefore obtains results that are more likely given the data.",

keywords = "pharmacokinetics",

author = "Tatiana Tatarinova and Roger Jelliffe and Michael Neely and Alan Schumitzky and David Bayard and Guilder, {Michael Van} and Andreas Botnen and Aida Bustad and Derek Laing and Walter Yamada and Jay Bartroff",

year = "2011",

month = apr,

day = "23",

doi = "10.1016/j.phrs.2011.04.008",

language = "English",

volume = "64",

journal = "Pharmacological Research",

issn = "1043-6618",

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TY - JOUR

T1 - Nonparametric population modeling and Bayesian analysis.

AU - Tatarinova, Tatiana

AU - Jelliffe, Roger

AU - Neely, Michael

AU - Schumitzky, Alan

AU - Bayard, David

AU - Guilder, Michael Van

AU - Botnen, Andreas

AU - Bustad, Aida

AU - Laing, Derek

AU - Yamada, Walter

AU - Bartroff, Jay

PY - 2011/4/23

Y1 - 2011/4/23

N2 - The nonparametric (NP) population modeling approach estimated the model parameter values and predicted the observed mycophenolic acid concentrations more precisely than the parametric method did. We expect this because the NP method makes no assumptions about the shape of the model parameter distributions, as parametric methods do, and therefore obtains results that are more likely given the data.

AB - The nonparametric (NP) population modeling approach estimated the model parameter values and predicted the observed mycophenolic acid concentrations more precisely than the parametric method did. We expect this because the NP method makes no assumptions about the shape of the model parameter distributions, as parametric methods do, and therefore obtains results that are more likely given the data.

KW - pharmacokinetics

U2 - 10.1016/j.phrs.2011.04.008

DO - 10.1016/j.phrs.2011.04.008

M3 - Article

C2 - 21699981

SN - 1043-6618

VL - 64

JO - Pharmacological Research

JF - Pharmacological Research

IS - 4

ER -

Nonparametric population modeling and Bayesian analysis.

Abstract

Keywords

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