Bayesian methods for nonignorable dropout in joint models in smoking cessation studies.

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Bayesian methods for nonignorable dropout in joint models in smoking cessation studies.

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2016 nî lūn-bûn

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2016年の論文

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2016年学术文章

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2016年学术文章

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2016年学术文章

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2016年学术文章

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2016年学术文章

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2016年学术文章

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2016年學術文章

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2016年學術文章

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Bayesian methods for nonignorable dropout in joint models in smoking cessation studies.

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Bayesian methods for nonignorable dropout in joint models in smoking cessation studies.

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Bayesian methods for nonignorable dropout in joint models in smoking cessation studies.

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Bayesian methods for nonignorable dropout in joint models in smoking cessation studies.

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Bayesian methods for nonignorable dropout in joint models in smoking cessation studies.

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Bayesian methods for nonignorable dropout in joint models in smoking cessation studies.

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P1476

Bayesian methods for nonignorable dropout in joint models in smoking cessation studies.

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P2093

B H Marcus

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J T Gaskins

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M J Daniels

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P2860

Slice sampling

Simulation of truncated normal variables

The horseshoe estimator for sparse signals

Marginally specified logistic-normal models for longitudinal binary data.

Rationale, design, and baseline data for Commit to Quit II: an evaluation of the efficacy of moderate-intensity physical activity as an aid to smoking cessation in women.

Modeling longitudinal data with nonignorable dropouts using a latent dropout class model.

Covariance Partition Priors: A Bayesian Approach to Simultaneous Covariance Estimation for Longitudinal Data.

Factor analytic models of clustered multivariate data with informative censoring.

A note on MAR, identifying restrictions, model comparison, and sensitivity analysis in pattern mixture models with and without covariates for incomplete data.

A Bayesian Shrinkage Model for Incomplete Longitudinal Binary Data with Application to the Breast Cancer Prevention Trial.

P304

1454-1465

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scholarly article

P356

10.1080/01621459.2016.1167693

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P407

English

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516

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P478

111

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P577

2016-01-01T00:00:00Z

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P698

29104333

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P932

5663304

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