Nonignorable dropout models for longitudinal binary data with random effects: An application of Monte Carlo approximation through the Gibbs output.
Jennifer So-Kuen ChanDoris Y. P. LeungS. T. Boris ChoyWai Y. WanPublished in: Comput. Stat. Data Anal. (2009)
Keyphrases
- monte carlo
- monte carlo simulation
- binary data
- random effects
- markovian decision
- importance sampling
- markov chain
- mixed effects
- particle filter
- monte carlo tree search
- markov chain monte carlo
- least squares
- data sets
- formal concept analysis
- model selection
- hidden markov models
- continuous data
- bayesian framework
- linear models
- hierarchical structure
- markov random field
- support vector
- machine learning
- data mining