A Bayesian approach to improved estimation of causal effect predictiveness for a principal surrogate endpoint
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Surrogates of protection in repeated low-dose challenge experiments.Evaluating principal surrogate endpoints with time-to-event data accounting for time-varying treatment efficacySurrogacy assessment using principal stratification when surrogate and outcome measures are multivariate normal.Surrogate Endpoint Evaluation: Principal Stratification Criteria and the Prentice Definition.Latent class instrumental variables: a clinical and biostatistical perspectiveComparing and combining biomarkers as principle surrogates for time-to-event clinical endpoints.Statistical approaches for evaluating surrogate outcomes in clinical trials: A systematic review.Surrogacy assessment using principal stratification with multivariate normal and Gaussian copula models.Validation of surrogate endpoints in cancer clinical trials via principal stratification with an application to a prostate cancer trial.Links between causal effects and causal association for surrogacy evaluation in a gaussian setting.Surrogacy assessment using principal stratification and a Gaussian copula model.Hard, harder, hardest: principal stratification, statistical identifiability, and the inherent difficulty of finding surrogate endpoints.Emotion regulation in children and adolescents with autism spectrum disorder.
P2860
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P2860
A Bayesian approach to improved estimation of causal effect predictiveness for a principal surrogate endpoint
description
2012 nî lūn-bûn
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2012年の論文
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2012年論文
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2012年論文
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name
A Bayesian approach to improve ...... a principal surrogate endpoint
@en
type
label
A Bayesian approach to improve ...... a principal surrogate endpoint
@en
prefLabel
A Bayesian approach to improve ...... a principal surrogate endpoint
@en
P2860
P1433
P1476
A Bayesian approach to improve ...... a principal surrogate endpoint
@en
P2093
Corwin M Zigler
Thomas R Belin
P2860
P304
P356
10.1111/J.1541-0420.2011.01736.X
P407
P577
2012-02-20T00:00:00Z