The analysis of correlated panel data using a continuous-time Markov model.

We consider the analysis of correlated panel data in which two or more correlated multistate processes are periodically observed on each individual and the exact transition times between states are unknown. We describe a procedure that models each process marginally under a time-homogeneous Markov model allowing for covariates. The resulting estimators are shown to be asymptotically jointly normal with a covariance matrix that can be consistently estimated. Simultaneous inference procedures are also proposed. Methods are illustrated using data from an AIDS clinical trial to compare the toxic effects of two treatments on two hematologic variables, hemoglobin and absolute neutrophil count.

[1]  Daniel O. Stram,et al.  Analysis of Repeated Ordered Categorical Outcomes with Possibly Missing Observations and Time-Dependent Covariates , 1988 .

[2]  D O Stram,et al.  Analysing repeated measurements with possibly missing observations by modelling marginal distributions. , 1988, Statistics in medicine.

[3]  J. Bartlett,et al.  Mortality in patients with the acquired immunodeficiency syndrome treated with either foscarnet or ganciclovir for cytomegalovirus retinitis , 1991 .

[4]  J P Klein,et al.  A biological marker model for predicting disease transitions. , 1984, Biometrics.

[5]  J F Lawless,et al.  Multi-state Markov models for analysing incomplete disease history data with illustrations for HIV disease. , 1994, Statistics in medicine.

[6]  K. Gabriel,et al.  On closed testing procedures with special reference to ordered analysis of variance , 1976 .

[7]  S. Holm.  A Simple Sequentially Rejective Multiple Test Procedure , 1979 .

[8]  L. J. Wei,et al.  Regression analysis of multivariate incomplete failure time data by modeling marginal distributions , 1989 .

[9]  J. Ward,et al.  Statistical analysis of the stages of HIV infection using a Markov model. , 1989, Statistics in medicine.

[10]  R Kay,et al.  A Markov model for analysing cancer markers and disease states in survival studies. , 1986, Biometrics.

[11]  David R. Cox,et al.  Regression models and life tables (with discussion , 1972 .

[12]  C. L. Chiang,et al.  An Introduction To Stochastic Processes And Their Applications | event.zain.com , 2021 .

[13]  J. Kalbfleisch,et al.  The Analysis of Panel Data under a Markov Assumption , 1985 .