Modelling placebo response in depression trials using a longitudinal model with informative dropout.
about
Handling missing data in a duloxetine population pharmacokinetic/pharmacodynamic model - imputation methods and selection models.Missing data in model-based pharmacometric applications: points to consider.Trajectories of depression severity in clinical trials of duloxetine: insights into antidepressant and placebo responses.Minimizing attrition bias: a longitudinal study of depressive symptoms in an elderly cohort.Colonic treatments and targets: issues and opportunities.Structural models describing placebo treatment effects in schizophrenia and other neuropsychiatric disorders.Modelling and simulation of placebo effect: application to drug development in schizophrenia.Exposure-response analysis after subcutaneous administration of RBP-7000, a once-a-month long-acting Atrigel formulation of risperidone.Model-based approaches to increase efficiency of drug development in schizophrenia: a can't miss opportunity.Performance of nonlinear mixed effects models in the presence of informative dropout.Joint modeling of efficacy, dropout, and tolerability in flexible-dose trials: a case study in depression.Development of a placebo effect model combined with a dropout model for bipolar disorder.Continuous-time Markov modelling of flexible-dose depression trials.Modelling and simulation of the Positive and Negative Syndrome Scale (PANSS) time course and dropout hazard in placebo arms of schizophrenia clinical trials.Declining efficacy in controlled trials of antidepressants: effects of placebo dropout.A PCA approach to population analysis: with application to a Phase II depression trial.General and comparative efficacy and effectiveness of antidepressants in the acute treatment of depressive disorders: a report by the WPA section of pharmacopsychiatry.
P2860
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P2860
Modelling placebo response in depression trials using a longitudinal model with informative dropout.
description
2008 nî lūn-bûn
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name
Modelling placebo response in ...... odel with informative dropout.
@en
Modelling placebo response in ...... odel with informative dropout.
@nl
type
label
Modelling placebo response in ...... odel with informative dropout.
@en
Modelling placebo response in ...... odel with informative dropout.
@nl
prefLabel
Modelling placebo response in ...... odel with informative dropout.
@en
Modelling placebo response in ...... odel with informative dropout.
@nl
P2093
P1476
Modelling placebo response in ...... odel with informative dropout.
@en
P2093
Agnes Lavergne
Emilio Merlo-Pich
Roberto Gomeni
P356
10.1016/J.EJPS.2008.10.025
P407
P577
2008-11-08T00:00:00Z