Abstract
This chapter discusses nonparametric or distribution-free comparison of several point or recurrent event processes when one observes only panel count data. As commented above, in the case of panel count data, it is very difficult or impossible to estimate the intensity process and in consequence, one usually focuses on the rate or mean functions of the underlying recurrent event processes of interest. For the same reason, with respect to the comparison of the processes, it is common and also convenient to formulate the null hypothesis using the mean functions.
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References
Balakrishnan, N. and Zhao, X. (2009). New multi-sample nonparametric tests for panel count data. The Annals of Statistics, 37, 1112–1149.
Balakrishnan, N. and Zhao, X. (2010a). A nonparametric test for the equality of counting processes with panel count data. Computational Statistics and Data Analysis, 54, 135–142.
Balakrishnan, N. and Zhao, X. (2010b). A class of multi-sample nonparametric tests for panel count data. Ann. Inst. Stat. Math.
Cook, R. J. and Lawless, J. F. (2007). The statistical analysis of recurrent events. Springer-Verlag, New York.
Davis, C. S. and Wei, L. J. (1988). Nonparametric methods for analyzing incomplete nondecreasing repeated measurements. Biometrics, 44, 1005–1018.
Kalbfleisch, J. D. and Prentice, R. L. (2002). The statistical analysis of failure time data. Second edition, John Wiley: New York.
Li, N., Sun, L. and Sun, J. (2010). Semiparametric transformation models for panel count data with dependent observation processes. Statistics in Biosciences, 2, 191–210.
Park, D-H. (2005). Semiparametric and nnonparametric methods for the analysis of longitudinal data. Ph.D. Dissertation, University of Missouri, Columbia.
Park, D-H., Sun, J. and Zhao, X. (2007). A class of two-sample nonparametric tests for panel count data. Communication in Statistics: Theory Methods, 36, 1611–1625.
Sun, J. (1999). A Nonparametric test for current status data with unequal censoring. J. R. Statist. Soc. B, 61, 243–250.
Sun, J. and Fang, H. B. (2003). A nonparametric test for panel count data. Biometrika, 90, 199–208.
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.
Sun, J and Rai, S. N. (2001). Nonparametric tests for the comparison of point processes based on incomplete data. Scand Journal Statistics, 28, 725–732.
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.
Zhang, Y. (2006). Nonparametric K-sample test with panel count data. Biometrika, 93, 777–790.
Zhao, H., Virkler, K. and Sun, J. (2013c). Nonparametric comparison for multivariate panel count data. Communications in Statistics - Theory and Methods, to appear.
Zhao, X. and Sun, J. (2011). Nonparametric comparison for panel count data with unequal observation processes. Biometrics, 67, 770–779.
Zhao, X., Balakrishnan, N. and Sun, J. (2011a). Nonparametric inference based on panel count data (with discussion). Test, 20, 1–71.
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Sun, J., Zhao, X. (2013). Nonparametric Comparison of Point Processes. In: Statistical Analysis of Panel Count Data. Statistics for Biology and Health, vol 80. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8715-9_4
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DOI: https://doi.org/10.1007/978-1-4614-8715-9_4
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