A transition copula model for analyzing multivariate longitudinal data with missing responses-Reference-Cited by-同舟云学术

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A transition copula model for analyzing multivariate longitudinal data with missing responses

Published:2021-05-28 Issue: Volume: Page:1-14
ISSN:0266-4763
Container-title:Journal of Applied Statistics
language:en
Short-container-title:Journal of Applied Statistics

Author:

Ahmadi A.¹,Baghfalaki T.¹,Ganjali M.²,Kabir A.³,Pazouki A.³⁴

Affiliation:

1. Department of Statistics, Faculty of Mathematical Sciences, Tarbiat Modares University, Tehran, Iran

2. Department of Statistics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran

3. Minimally Invasive Surgery Research Center, Iran University of Medical Sciences, Tehran, Iran

4. Center of Excellence of European Branch of International Federation for Surgery of Obesity, Iran University of Medical Sciences, Tehran, Iran

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/02664763.2021.1931055

Reference19 articles.

1. Multiple imputation by chained equations: what is it and how does it work?

2. A transition model for analyzing multivariate longitudinal data using Gaussian copula approach

3. Nonparametric estimation of copula functions for dependence modelling

4. Copula-based regression models for a bivariate mixed discrete and continuous outcome

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