Random effects and latent processes approaches for analyzing binary longitudinal data with missingness: a comparison of approaches using opiate clinical trial data
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Summary
Various random effects and latent process models which have been proposed for analyzing longitudinal binary data subject to both non-ignorable intermittent missing data and dropout are discussed.
- Type
- article
- Published
- 2007-10-01
- Cited by
- 21
- References
- 23
- OpenAlex
- https://openalex.org/W17656452
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:23789388
Keywords
Mathematics, Zero (linguistics), Humanities, Philosophy, Linguistics
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Cited by
- Complex models and computational methods in statistics
- A TWO-STATE MIXED HIDDEN MARKOV MODEL FOR RISKY TEENAGE DRIVING BEHAVIOR
- Joint Analysis of Survival Time and Longitudinal Categorical Outcomes
- A review of multivariate longitudinal data analysis
- Handling non-ignorable dropouts in longitudinal data: a conditional model based on a latent Markov heterogeneity structure
- Modified weights based generalized quasilikelihood inferences in incomplete longitudinal binary models
- Bayesian informative dropout model for longitudinal binary data with random effects using conditional and joint modeling approaches
- Handling initial conditions and endogenous covariates in dynamic/transition models for binary data with unobserved heterogeneity
- A Bayesian Modeling of Monotonic Ordinal Responses with Application to Maturation
- Penalized Likelihood Approach for Simultaneous Analysis of Survival Time and Binary Longitudinal Outcome
- Joint Modeling of Survival Time and Longitudinal Outcomes with Flexible Random Effects
- A multilevel latent Markov model for the evaluation of nursing homes' performance
- Shared random parameter models: A legacy of the biostatistics program at the National Heart, Lung, and Blood Institute
- Statistical Methods for Joint Analysis of Survival Time and Longitudinal Data
- A Likelihood-Based Approach with Shared Latent Random Parameters for the Longitudinal Binary and Informative Censoring Processes
- Regression analysis of interval-censored failure time data with time-dependent covariates
- A Comparison of Mathematical and Statistical Modeling with Longitudinal Data: An Application to Ecological Momentary Assessment of Behavior Change in Individuals with Alcohol Use Disorder
- Innovative Applications of Shared Random Parameter Models for Analyzing Longitudinal Data Subject to Dropout
- Classification of Multivariate Linear-Circular Data with Nonignorable Missing Values
- Latent variable and structural equation models
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