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Erschienen in:
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2013 | OriginalPaper | Buchkapitel

1. Introduction

verfasst von : Jianguo Sun, Xingqiu Zhao

Erschienen in: Statistical Analysis of Panel Count Data

Verlag: Springer New York

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Abstract

The event history study refers to the study concerning the patterns of the occurrences of certain events and is often seen in many fields. Among them, two that have seen or used such studies most are probably medical research and social sciences (Allison, 1984; Kalbfleisch and Prentice, 2002; Klein and Moeschberger, 2003; Nelson, 2003; Vermunt, 1997; Yamaguchi, 1991). In medical research, the event under study can be the occurrence of a disease or death, the hospitalization of certain patient, or the occurrence of some infection. In social sciences, examples of the subjects for event history studies include occurrence rates of births, deaths, marriages and divorces in demographic studies, and the employment or unemployment history of certain populations in social studies. In addition to these two, other fields that often see event history studies include reliability studies and tumorigenicity experiments.

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Nächstes Kapitel Poisson Models and Parametric Inference
Literatur
Aalen, O. O. (1975). Statistical inference for a family of counting processes. Ph.D. Thesis, University of California, Berkeley.
Allison, P. D. (1984). Event history analysis: regression for longitudinal event data. Sage Publications, Inc.
Andersen, P. K. and Borgan, O. (1985). Counting process models for life history data: a review. Scand. J. Stat. 12, 97–158.
Andersen, P. K., Borgan, O., Gill, R. D. and Keiding, N. (1993). Statistical models based on counting processes. Springer-Verlag, New York.CrossRefMATH
Andersen, P. K. and Gill, R. D. (1982). Cox’s regression model for counting processes: A large sample study. The Annals of Statistics, 10, 1100–1120.MathSciNetCrossRefMATH
Andrews, D. F. and Herzberg, A. M. (1985). Data: A collection of problems from many fields for the student and research worker. Springer-Verlag, New York.CrossRefMATH
Byar, D. P. (1980). The veterans administration study of chemoprophylaxis for recurrent stage I bladder tumors: comparison of placebo, pyridoxine, and topical thiotepa. In Bladder Tumors and Other Topics in Urological Oncology, eds. Pavone-Macaluso, M., Smith, P. H. and Edsmyn, F., New York: Plenum, 363–370.
Byar, D. P., Blackard, C. and The Veterans Administration Cooperative Urological Research Group (1977). Comparisons of placebo, pyridoxine, and topical thiotepa in preventing recurrence of stage I bladder cancer. Urology, 10, 556–561.CrossRef
Cook, R. J. and Lawless, J. F. (1996). Interim monitoring of longitudinal comparative studies with recurrent event responses. Biometrics, 52, 1311–1323.CrossRefMATH
Cook, R. J. and Lawless, J. F. (2007). The statistical analysis of recurrent events. Springer-Verlag, New York.MATH
Cox, D. R. and Miller, H. D. (1965). The theory of stochastic processes. London: Chapman and Hall.MATH
Diamond, I. D. and McDonald, J. W. (1991). The analysis of current status data. In Demographic Applications of Event History Analysis, eds. Trussel J, Hankinson R, Tilton, J, Oxford University Press, Oxford, U.K.
Freireich, E. O. et al. (1963). The effect of 6-mercaptopmine on the duration of steroid induced remission in acute leukemia. Blood, 21, 699–716.
Gail, M. H., Santner, T. J. and Brown, C. C. (1980). An analysis of comparative carcinogenesis experiments based on multiple times to tumor. Biometrics, 36, 255–266.MathSciNetCrossRefMATH
Gaver, D. P. and O’Muircheartaigh, I. G. (1987). Robust empirical Bayes analyses of event rates. Technometrics, 29, 1–15.MathSciNetCrossRefMATH
Gehan, E. A. (1965). A generalized Wilcoxon test for comparing arbitrarily singly-censored samples. Biometrika, 52, 203–223.MathSciNetMATH
He, X., Tong, X. and Sun, J. (2009). Semiparametric analysis of panel count data with correlated observation and follow-up times. Lifetime Data Analysis, 15, 177–196.MathSciNetCrossRefMATH
Hu, X. J., Sun, J. and Wei, L. J. (2003). Regression parameter estimation from panel counts. Scand. Journal of Statistics, 30, 25–43.MathSciNetCrossRefMATH
Huang, C. Y., Wang, M. C. and Zhang, Y. (2006). Analyzing panel count data with informative observation times. Biometrika, 93, 763–775.MathSciNetCrossRef
Kalbfleisch, J. D. and Lawless, J. F. (1985). The analysis of panel data under a Markov assumption. Journal of the American Statistical Association, 80, 863–871.MathSciNetCrossRefMATH
Kalbfleisch, J. D., Lawless, J. F. and Robinson, J. A. (1991). Methods for the analysis and prediction of warranty claims. Technometrics, 33, 273–285.CrossRefMATH
Kalbfleisch, J. D. and Prentice, R. L. (2002). The statistical analysis of failure time data. Second edition, John Wiley: New York.CrossRefMATH
Klein, J. P. and Moeschberger, M. L. (2003). Survival analysis, Springer-Verlag: New York.MATH
Lawless, J. F. and Nadeau, J. C. (1995). Some simple robust methods for the analysis of recurrent events. Technometrics, 37, 158–168.MathSciNetCrossRefMATH
Lawless, J. F. and Zhan, M. (1998). Analysis of interval-grouped recurrent-event data using piecewise constant rate functions. Canadian Journal of Statistics, 26, 549–565.CrossRefMATH
Lee, L-Y. (2008). Nonparametric and semiparametric models for multivariate panel count data. Ph.D. Dissertation, University of Wisconsin-Madison.
Li, N. (2011). Semiparametric transformation models for panel count data. Ph.D. Dissertation, University of Missouri, Columbia.
Lin, D. Y., Wei, L. J., Yang, I. and Ying, Z. (2000). Semiparametric regression for the mean and rate functions of recurrent events. Journal of Royal Statistical Society Ser B, 62, 711–730.MathSciNetCrossRefMATH
Nelson, W. B. (2003). Recurrent events data analysis for product repairs, disease recurrences, and other applications. ASA-SIAM Series on Statistics and Applied Probability, 10.
Pepe, M. S. and Cai, J. (1993). Some graphical displays and marginal regression analyses for recurrent failure times and time dependent covariates. Journal of the American Statistical Association, 88, 811–820.CrossRefMATH
Sun, J. (2006). The statistical analysis of interval-censored failure time data. Springer: New York.MATH
Sun, J. (2009). Panel count data. Handbook of Statistical Methods in Life and Health Sciences, Editor: Balakrishnan, N., John Wiley & Sons. Ltd.
Sun, J. and Kalbfleisch, J. D. (1993). The analysis of current status data on point processes. Journal of the American Statistical Association, 88, 1449–1454.MathSciNetCrossRefMATH
Sun, J. and Kalbfleisch, J. D. (1995). Estimation of the mean function of point processes based on panel count data. Statistica Sinica, 5, 279–290.MathSciNetMATH
Sun, J., Tong, X. and He, X. (2007b). Regression analysis of panel count data with dependent observation times. Biometrics, 63, 1053–1059.MathSciNetCrossRefMATH
Sun, J. and Wei, L. J. (2000). Regression analysis of panel count data with covariate-dependent observation and censoring times. Journal of the Royal Statistical Society, Series B, 62, 293–302.MathSciNetCrossRef
Thall, P. F. (1988). Mixed Poisson likelihood regression models for longitudinal interval count data. Biometrics, 44, 197–209.MathSciNetCrossRefMATH
Thall, P. F. and Lachin, J. M. (1988). Analysis of recurrent events: nonparametric methods for random-interval count data. Journal of the American Statistical Association, 83, 339–347.CrossRef
Vermunt, J. K. (1997). Log-linear models for event histories. Sage Publications Inc: Newbury Park, CA.
Wang, M. C. and Chen, Y. Q. (2000). Nonparametric and semiparametric trend analysis of stratified recurrence time data. Biometrics, 56, 789–794.CrossRefMATH
Wang, M. C., Qin, J. and Chiang, C. T. (2001). Analyzing recurrent event data with informative censoring. Journal of the American Statistical Association, 96, 1057–1065.MathSciNetCrossRefMATH
Wellner, J. A. and Zhang, Y. (2007). Two likelihood-based semiparametric estimation methods for panel count data with covariates. The Annals of Statistics, 35, 2106–2142.MathSciNetCrossRefMATH
Yamaguchi, K. (1991). Event history analysis. Sage Publications, Inc.
Zhao, X., Balakrishnan, N. and Sun, J. (2011a). Nonparametric inference based on panel count data (with discussion). Test, 20, 1–71.MathSciNetCrossRef
Metadaten
Titel
Introduction
verfasst von
Jianguo Sun
Xingqiu Zhao
Copyright-Jahr
2013
Verlag
Springer New York
Buch
Statistical Analysis of Panel Count Data

Print ISBN: 978-1-4614-8714-2

Electronic ISBN: 978-1-4614-8715-9

Copyright-Jahr: 2013

DOI
https://doi.org/10.1007/978-1-4614-8715-9_1