• 1
  • 2
  • 5
  • 6
  • 7
  • 8
  • 9
  • 3
  • 4
IPM
30
YEARS OLD

“School of Biological”

Back to Papers Home
Back to Papers of School of Biological

Paper   IPM / Biological / 15493
School of Biological Sciences
  Title:   A transition model for analyzing multivariate longitudinal data using Gaussian copula approach
  Author(s): 
1 . Taban Baghfalaki
2 . Mojtaba Ganjali
  Status:   Published
  Journal: Advances in Statistical Analysis
  Vol.:  https://doi.org/10.1007/s10182-018-00346-w
  Year:  2019
  Pages:   1-55
  Supported by:  IPM
  Abstract:
Longitudinal studies often involve multiple mixed response variables measured repeatedly over time. Although separate modeling of these multiple mixed response variables can be easily performed, they may lead to inefficient estimates and consequently, misleading inferences. For obtaining correct inference, one needs to model multiple mixed responses jointly. In this paper, we use copula models for defining a multivariate distribution for multiple mixed outcomes at each time point. Then, we use transition model for considering association between longitudinal measurements. Two simulation studies are performed for illustration of the proposed approach. The results of the simulation studies show that the use of the separate models instead of the joint modeling leads to inefficient parameter estimates. The proposed approach is also used for analyzing two real data sets. The first data set is a part of the British Household Panel Survey. In this data set, annual income and life satisfaction are considered as the continuous and the ordinal correlated longitudinal responses, respectively. The second data set is a longitudinal data about heart failure patients. This study is a treatment–control study, where the effect of a treatment is simultaneously investigated on readmission and referral to doctor as two binary associated longitudinal responses.

Download TeX format
back to top
Clients Logo
Clients Logo
Clients Logo
Clients Logo
Clients Logo
Clients Logo
Clients Logo
Clients Logo
scroll left or right