Publications Search - Abstract View
| Title: |
Bayesian inference for smoking cessation with a latent cure state. |
| Authors: |
Luo S, Crainiceanu CM, Louis TA, Chatterjee N |
| Journal: |
Biometrics |
| Date: |
2009 Sep |
| Branches: |
BB |
| PubMed ID: |
19173701 |
| PMC ID: |
not available |
| Abstract: |
We present a Bayesian approach to modeling dynamic smoking addiction behavior processes when cure is not directly observed due to censoring. Subject-specific probabilities model the stochastic transitions among three behavioral states: smoking, transient quitting, and permanent quitting (absorbent state). A multivariate normal distribution for random effects is used to account for the potential correlation among the subject-specific transition probabilities. Inference is conducted using a Bayesian framework via Markov chain Monte Carlo simulation. This framework provides various measures of subject-specific predictions, which are useful for policy-making, intervention development, and evaluation. Simulations are used to validate our Bayesian methodology and assess its frequentist properties. Our methods are motivated by, and applied to, the Alpha-Tocopherol, Beta-Carotene Lung Cancer Prevention study, a large (29,133 individuals) longitudinal cohort study of smokers from Finland. |