Model-Based Approach to Predict Adherence to Protocol During Antiobesity Trials.

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Model-Based Approach to Predict Adherence to Protocol During Antiobesity Trials.

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2017 nî lūn-bûn

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2017年の論文

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2017年論文

@yue

2017年論文

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2017年論文

@zh-hk

2017年論文

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2017年論文

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2017年论文

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2017年论文

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Model-Based Approach to Predict Adherence to Protocol During Antiobesity Trials.

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Model-Based Approach to Predict Adherence to Protocol During Antiobesity Trials.

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Model-Based Approach to Predict Adherence to Protocol During Antiobesity Trials.

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P1476

Model-Based Approach to Predict Adherence to Protocol During Antiobesity Trials

@en

P2093

Gezim Lahu

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Lawrence J Lesko

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Majid Vakilynejad

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Mirjam N Trame

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Vishnu D Sharma

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P2860

The medical care costs of obesity: An instrumental variables approach

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Prevalence of obesity and trends in body mass index among US children and adolescents, 1999-2010

Simultaneous vs. sequential analysis for population PK/PD data I: best-case performance.

Design evaluation and optimisation in multiple response nonlinear mixed effect models: PFIM 3.0.

Markov chains and semi-Markov models in time-to-event analysis.

The use of the SAEM algorithm in MONOLIX software for estimation of population pharmacokinetic-pharmacodynamic-viral dynamics parameters of maraviroc in asymptomatic HIV subjects.

A randomized, phase 3 trial of naltrexone SR/bupropion SR on weight and obesity-related risk factors (COR-II)

Cause-specific excess deaths associated with underweight, overweight, and obesity.

P304

240-253

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P31

scholarly article

P356

10.1002/JCPH.994

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P433

http://www.w3.org/2001/XMLSchema#string

P478

http://www.w3.org/2001/XMLSchema#string

P50

François Pierre Combes

P577

2017-08-31T00:00:00Z

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P698

28858397

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P932

5811797

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