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Robust Bayesian inference for multivariate longitudinal data by using normal/independent distributions.

Publication ,  Journal Article
Luo, S; Ma, J; Kieburtz, KD
Published in: Stat Med
September 30, 2013

Many randomized clinical trials collect multivariate longitudinal measurements in different scales, for example, binary, ordinal, and continuous. Multilevel item response models are used to evaluate the global treatment effects across multiple outcomes while accounting for all sources of correlation. Continuous measurements are often assumed to be normally distributed. But the model inference is not robust when the normality assumption is violated because of heavy tails and outliers. In this article, we develop a Bayesian method for multilevel item response models replacing the normal distributions with symmetric heavy-tailed normal/independent distributions. The inference is conducted using a Bayesian framework via Markov Chain Monte Carlo simulation implemented in BUGS language. Our proposed method is evaluated by simulation studies and is applied to Earlier versus Later Levodopa Therapy in Parkinson's Disease study, a motivating clinical trial assessing the effect of Levodopa therapy on the Parkinson's disease progression rate.

Duke Scholars

Published In

Stat Med

DOI

EISSN

1097-0258

Publication Date

September 30, 2013

Volume

32

Issue

22

Start / End Page

3812 / 3828

Location

England

Related Subject Headings

  • Statistics & Probability
  • Randomized Controlled Trials as Topic
  • Quality of Life
  • Parkinson Disease
  • Multivariate Analysis
  • Monte Carlo Method
  • Models, Statistical
  • Markov Chains
  • Longitudinal Studies
  • Levodopa
 

Citation

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ICMJE
MLA
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Luo, S., Ma, J., & Kieburtz, K. D. (2013). Robust Bayesian inference for multivariate longitudinal data by using normal/independent distributions. Stat Med, 32(22), 3812–3828. https://doi.org/10.1002/sim.5778
Luo, Sheng, Junsheng Ma, and Karl D. Kieburtz. “Robust Bayesian inference for multivariate longitudinal data by using normal/independent distributions.Stat Med 32, no. 22 (September 30, 2013): 3812–28. https://doi.org/10.1002/sim.5778.
Luo, Sheng, et al. “Robust Bayesian inference for multivariate longitudinal data by using normal/independent distributions.Stat Med, vol. 32, no. 22, Sept. 2013, pp. 3812–28. Pubmed, doi:10.1002/sim.5778.
Journal cover image

Published In

Stat Med

DOI

EISSN

1097-0258

Publication Date

September 30, 2013

Volume

32

Issue

22

Start / End Page

3812 / 3828

Location

England

Related Subject Headings

  • Statistics & Probability
  • Randomized Controlled Trials as Topic
  • Quality of Life
  • Parkinson Disease
  • Multivariate Analysis
  • Monte Carlo Method
  • Models, Statistical
  • Markov Chains
  • Longitudinal Studies
  • Levodopa