Joint modeling of longitudinal count and time-to-event data with excess zero using accelerated failure time model: an application with CD4 cell counts
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Publication:5104526
DOI10.1080/03610926.2021.1872635OpenAlexW3124667371MaRDI QIDQ5104526
Ehsan Bahrami Samani, Mojtaba Zeinali Najafabadi, Mojtaba Ganjali
Publication date: 14 September 2022
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2021.1872635
joint modellongitudinal count dataaccelerated failure time (AFT)generalized linear mixed effect model (GLMEM)power series distribution (PSD)time to event (TTE) data
Uses Software
Cites Work
- Analysis of zero-adjusted count data
- Estimating regression parameters using linear rank tests for censored data
- Survival analysis. Techniques for censored and truncated data.
- Models for discrete longitudinal data.
- Joint Models for Longitudinal and Time-to-Event Data
- Joint modelling of longitudinal and time-to-event data with application to predicting abdominal aortic aneurysm growth and rupture
- Joint modelling of accelerated failure time and longitudinal data
- Linear regression with censored data
- Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing
- A Joint Model for Survival and Longitudinal Data Measured with Error
- Rank-based inference for the accelerated failure time model
- Jointly Modeling Longitudinal and Event Time Data With Application to Acquired Immunodeficiency Syndrome
- Zero‐Inflated Poisson and Binomial Regression with Random Effects: A Case Study
- Modeling the Relationship of Survival to Longitudinal Data Measured with Error. Applications to Survival and CD4 Counts in Patients with AIDS
- Modelling Progression of CD4-Lymphocyte Count and Its Relationship to Survival Time
- Likelihood estimation for longitudinal zero-inflated power series regression models
- Joint Models for Multivariate Longitudinal and Multivariate Survival Data
- Random effect models for repeated measures of zero-inflated count data
- A Flexible B‐Spline Model for Multiple Longitudinal Biomarkers and Survival
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