Design of Panel Studies for Disease Progression with Multiple Stages

A panel study consists of individuals who have data collected at periodic follow-up visits or pre-specified time points following entry into the study. The objective of this paper is to consider design issues in a panel study when the response variable is the stage of disease, and with focus on the transition intensities. Important design issues include the choice of the time interval between follow-up visits and sample size considerations. We study the effects of time intervals between follow-up visits on the precision of the transition intensities estimators. We also consider the power of statistical tests on the ratio of transition intensities. Discussion is extended to incorporate heterogeneity in the population in which frailty is introduced to describe subject-specific transition intensities.

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

[2]  G A Satten,et al.  Fitting Semi‐Markov Models to Interval‐Censored Data with Unknown Initiation Times , 1999, Biometrics.

[3]  M H Gail,et al.  Evaluating serial cancer marker studies in patients at risk of recurrent disease. , 1981, Biometrics.

[4]  Richard J. Cook,et al.  Some comments on efficiency gains from auxiliary information for right-censored data , 2001 .

[5]  J. Morris.  The Clinical Dementia Rating (CDR) , 1993, Neurology.

[6]  G A Satten,et al.  Estimating the Extent of Tracking in Interval‐Censored Chain‐Of‐Events Data , 1999, Biometrics.

[7]  S W Lagakos,et al.  A stochastic model for censored-survival data in the presence of an auxiliary variable. , 1976, Biometrics.

[8]  Erhan Çinlar,et al.  Introduction to stochastic processes , 1974 .

[9]  S W Lagakos,et al.  Using auxiliary variables for improved estimates of survival time. , 1977, Biometrics.

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

[11]  P. Hougaard,et al.  Fisher Information for Two Gamma Frailty Bivariate Weibull Models , 2000, Lifetime data analysis.

[12]  C. P. Hughes,et al.  A New Clinical Scale for the Staging of Dementia , 1982, British Journal of Psychiatry.

[13]  T. W. Anderson.  An Introduction to Multivariate Statistical Analysis , 1959 .

[14]  R. Chappell.  Sampling design of multiwave studies with an application to the Massachusetts health care panel study , 1991 .

[15]  T. W. Anderson,et al.  An Introduction to Multivariate Statistical Analysis , 1959 .

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

[17]  O. Aalen,et al.  Heterogeneity in survival analysis. , 1988, Statistics in medicine.

[18]  Philip Hougaard,et al.  Life table methods for heterogeneous populations: Distributions describing the heterogeneity , 1984 .

[19]  P. Albert,et al.  The design of a panel study under an alternating Poisson process assumption. , 1991, Biometrics.