A Stochastic Model for Analysis of Longitudinal AIDS Data

A Stochastic Model for Analysis of Longitudinal AIDS Data J. M. G. Taylor; W. G. Cumberland; J. P. Sy Journal of the American Statistical Association, Vol. 89, No. 427. (Sep., 1994), pp. 727-736. Stable URL: http://links.jstor.org/sici?sici=0162-1459%28199409%2989%3A427%3C727%3AASMFAO%3E2.0.CO%3B2-1 Journal of the American Statistical Association is currently published by American Statistical Association. Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at http://www.jstor.org/journals/astata.html. Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission. The JSTOR Archive is a trusted digital repository providing for long-term preservation and access to leading academic journals and scholarly literature from around the world. The Archive is supported by libraries, scholarly societies, publishers, and foundations. It is an initiative of JSTOR, a not-for-profit organization with a mission to help the scholarly community take advantage of advances in technology. For more information regarding JSTOR, please contact support@jstor.org. http://www.jstor.org Fri Feb 1 17:20:45 2008

[1]  S. Schach Weak Convergence Results for a Class of Multivariate Markov Processes , 1971 .

[2]  W. Cumberland,et al.  A multivariate model for growth of populations. , 1977, Theoretical population biology.

[3]  C. A. McMahan An Index of Tracking , 1981 .

[4]  J. Ware,et al.  Tracking: Prediction of Future Values from Serial Measurements , 1981 .

[5]  M. A. Foulkes,et al.  An index of tracking for longitudinal data , 1981 .

[6]  J. Ware,et al.  Random-effects models for longitudinal data. , 1982, Biometrics.

[7]  W. Cumberland,et al.  Weak convergence of an autoregressive process used in modeling population growth , 1982, Journal of Applied Probability.

[8]  R. Royall Model robust confidence intervals using maximum likelihood estimators , 1986 .

[9]  R. Jennrich,et al.  Unbalanced repeated-measures models with structured covariance matrices. , 1986, Biometrics.

[10]  J. Phair,et al.  The Multicenter AIDS Cohort Study: rationale, organization, and selected characteristics of the participants. , 1987, American journal of epidemiology.

[11]  P. Diggle An approach to the analysis of repeated measurements. , 1988, Biometrics.

[12]  J. Phair,et al.  Predictors of decline in CD4 lymphocytes in a cohort of homosexual men infected with human immunodeficiency virus. , 1988, Journal of acquired immune deficiency syndromes.

[13]  D. Bates,et al.  Newton-Raphson and EM Algorithms for Linear Mixed-Effects Models for Repeated-Measures Data , 1988 .

[14]  N. Jewell,et al.  Patterns of T lymphocyte changes with human immunodeficiency virus infection: from seroconversion to the development of AIDS. , 1989, Journal of acquired immune deficiency syndromes.

[15]  G. Reinsel,et al.  Models for Longitudinal Data with Random Effects and AR(1) Errors , 1989 .

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

[17]  S. Berman A stochastic model for the distribution of HIV latency time based on T4 counts , 1990 .

[18]  Cullis Br,et al.  A model for the analysis of growth data from designed experiments. , 1990 .

[19]  C. Mcgilchrist,et al.  A model for the analysis of growth data from designed experiments. , 1990, Biometrics.

[20]  R. H. Jones,et al.  Unequally spaced longitudinal data with AR(1) serial correlation. , 1991, Biometrics.

[21]  R. Detels,et al.  Applications of a computer simulation model of the natural history of CD4 T-cell number in HIV-infected individuals. , 1991, AIDS.

[22]  Christine A. Lee,et al.  Serial CD4 lymphocyte counts and development of AIDS , 1991, The Lancet.

[23]  U. Dafni,et al.  Modeling the Progression of HIV Infection , 1991 .

[24]  A. Gelfand,et al.  Hierarchical Bayes Models for the Progression of HIV Infection Using Longitudinal CD4 T-Cell Numbers , 1992 .

[25]  Jeremy MG Taylor,et al.  Semi Parametric Estimation of the Incubation Period of AIDS , 1992 .

[26]  M. Wulfsohn,et al.  The Relationship of CD4 Counts over Time to Survival in Patients with AIDS: Is CD4 a Good Surrogate Marker? , 1992 .

[27]  J. Margolick,et al.  Changes in T and non-T lymphocyte subsets following seroconversion to HIV-1: stable CD3+ and declining CD3- populations suggest regulatory responses linked to loss of CD4 lymphocytes. The Multicenter AIDS Cohort Study. , 1993, Journal of acquired immune deficiency syndromes.

[28]  J. Nielsen,et al.  Marker-dependent hazard estimation: an application to AIDS. , 1993, Statistics in medicine.

[29]  D. Lin,et al.  Evaluating the role of CD4-lymphocyte counts as surrogate endpoints in human immunodeficiency virus clinical trials. , 1993, Statistics in medicine.

[30]  J. Taylor,et al.  Smoothing grouped bivariate data to obtain the incubation period distribution of AIDS. , 1994, Statistics in medicine.