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Semiparametric Regression Analysis of Panel Count Data: A Practical Review

dc.contributor.authorChiou, Sy Han
dc.contributor.authorHuang, Chiung‐yu
dc.contributor.authorXu, Gongjun
dc.contributor.authorYan, Jun
dc.date.accessioned2019-05-31T18:24:57Z
dc.date.available2020-06-01T14:50:01Zen
dc.date.issued2019-04
dc.identifier.citationChiou, Sy Han; Huang, Chiung‐yu ; Xu, Gongjun; Yan, Jun (2019). "Semiparametric Regression Analysis of Panel Count Data: A Practical Review." International Statistical Review 87(1): 24-43.
dc.identifier.issn0306-7734
dc.identifier.issn1751-5823
dc.identifier.urihttps://hdl.handle.net/2027.42/149207
dc.publisherCambridge University Press
dc.publisherWiley Periodicals, Inc.
dc.subject.otherrecurrent event
dc.subject.otherCounting process
dc.subject.otherestimating equation
dc.subject.otherfrailty
dc.subject.othermaximum likelihood
dc.titleSemiparametric Regression Analysis of Panel Count Data: A Practical Review
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelStatistics (Mathematical)
dc.subject.hlbtoplevelScience
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/149207/1/insr12271_am.pdf
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/149207/2/insr12271.pdf
dc.identifier.doi10.1111/insr.12271
dc.identifier.sourceInternational Statistical Review
dc.identifier.citedreferenceTherneau, T.M. ( 2015 ). A package for survival analysis in S. version 2.38.
dc.identifier.citedreferencePrentice, R.L., Williams, B.J. & Peterson, A.V. ( 1981 ). On the regression analysis of multivariate failure time data. Biometrika, 68 ( 2 ), 373 â 379.
dc.identifier.citedreferenceR Core Team ( 2017 ). R: A Language and Environment for Statistical Computing., R Foundation for Statistical Computing: Vienna, Austria.
dc.identifier.citedreferenceRamsay, J.O. ( 1988 ). Monotone regression splines in action. Statist. Sci., 3, 425 â 441.
dc.identifier.citedreferenceRiphahn, R.T., Wambach, A. & Million, A. ( 2003 ). Incentive effects in the demand for health care: A bivariate panel count data estimation. J. Appl. Econometrics, 18 ( 4 ), 387 â 405.
dc.identifier.citedreferenceSun, J., Tong, X. & He, X. ( 2007 ). Regression analysis of panel count data with dependent observation times. Biometrics, 63 ( 4 ), 1053 â 1059.
dc.identifier.citedreferenceSun, J. & Wei, L.J. ( 2000 ). Regression analysis of panel count data with covariateâ dependent observation and censoring times. J. R. Stat. Soc. Ser. B, 62 ( 2 ), 293 â 302.
dc.identifier.citedreferenceSun, J. & Zhao, X. ( 2013 ). Statistical analysis of panel count data. Springer: New York.
dc.identifier.citedreferenceTurnbull, B.W. ( 1976 ). The empirical distribution function with arbitrarily grouped, censored and truncated data. J. R. Stat. Soc. Ser. B, 38 ( 3 ), 290 â 295.
dc.identifier.citedreferenceVaradhan, R. & Roland, C. ( 2008 ). Simple and globally convergent methods for accelerating the convergence of any EM algorithm. Scand. J. Stat., 35 ( 2 ), 335 â 353.
dc.identifier.citedreferenceWang, X., Ma, S. & Yan, J. ( 2013 ). Augmented estimating equations for semiparametric panel count regression with informative observation times and censoring time. Statist. Sinica, 23, 359 â 381.
dc.identifier.citedreferenceWang, X. & Yan, J. ( 2011 ). Fitting semiparametric regressions for panel count survival data with an R package spef. Computer Methods and Programs in Biomedicine, 104 ( 2 ), 278 â 285.
dc.identifier.citedreferenceWellner, J.A. & Zhang, Y. ( 2000 ). Two estimators of the mean of a counting process with panel count data. Ann. Statist., 28, 779 â 814.
dc.identifier.citedreferenceWellner, J.A. & Zhang, Y. ( 2007 ). Two likelihoodâ based semiparametric estimation methods for panel count data with covariates. Ann. Statist., 35 ( 5 ), 2106 â 2142.
dc.identifier.citedreferenceWickham, H. ( 2009 ). ggplot2: Elegant Graphics for Data Analysis. Springerâ Verlag: New York.
dc.identifier.citedreferenceXu, G., Chiou, S.H., Huang, C.â Y., Wang, M.â C. & Yan, J. ( 2017 ). Joint scaleâ change models for recurrent events and failure time. J. Amer. Statist. Assoc., 112, 794 â 805.
dc.identifier.citedreferenceYao, B. & Wang, L. ( 2014 ). PCDSpline: Semiparametric regression analysis of panel count data using monotone splines. R package version 1.0.
dc.identifier.citedreferenceYao, B., Wang, L. & He, X. ( 2016 ). Semiparametric regression analysis of panel count data allowing for withinâ subject correlation. Comput. Stat. Data Anal., 97, 47 â 59.
dc.identifier.citedreferenceZhang, Y. ( 2002 ). A semiparametric pseudolikelihood estimation method for panel count data. Biometrika, 89 ( 1 ), 39 â 48.
dc.identifier.citedreferenceZhang, Y. ( 2006 ). Nonparametric kâ sample tests with panel count data. Biometrika, 93 ( 4 ), 777 â 790.
dc.identifier.citedreferenceZhang, H., Zhao, H., Sun, J., Wang, D. & Kim, K. ( 2013 ). Regression analysis of multivariate panel count data with an informative observation process. J. Multivariate Anal., 119, 71 â 80.
dc.identifier.citedreferenceZhao, X., Tong, X. & Sun, J. ( 2013 ). Robust estimation for panel count data with informative observation times. Comput. Stat. Data Anal., 57 ( 1 ), 33 â 40.
dc.identifier.citedreferenceZhu, L., Tong, X., Zhao, H., Sun, J., Srivastava, D.K., Leisenring, W. & Robison, L.L. ( 2013 ). Statistical analysis of mixed recurrent event data with application to cancer survivor study. Stat. Med., 32 ( 11 ), 1954 â 1963.
dc.identifier.citedreferenceAndersen, P.K. & Gill, R.D. ( 1982 ). Cox’s regression model for counting processes: A large sample study. Ann. Statist., 10, 1100 â 1120.
dc.identifier.citedreferenceBailey, H.H., Kim, K., Verma, A.K., Sielaff, K., Larson, P.O., Snow, S., Lenaghan, T., Viner, J.L., Douglas, J. & Dreckschmidt, N.E. ( 2010 ). A randomized, doubleâ blind, placeboâ controlled phase 3 skin cancer prevention study of α â difluoromethylornithine in subjects with previous history of skin cancer. Cancer Prev. Res., 3 ( 1 ), 35 â 47.
dc.identifier.citedreferenceBarzilai, J. & Borwein, J.M. ( 1988 ). Twoâ point step size gradient methods. IMA J. Numer. Anal., 8 ( 1 ), 141 â 148.
dc.identifier.citedreferenceChiou, S.H., Wang, X. & Yan, J. ( 2017 ). spef: Semiparametric estimating functions. R package version 1.0â 6.
dc.identifier.citedreferenceChiou, S., Xu, G., Yan, J. & Huang, C.â Y. ( 2017 ). Semiparametric estimation of the accelerated mean model with panel count data under informative examination times. Biometrics. To appear. https://doi.org/10.1111/biom.12840
dc.identifier.citedreferenceCroissant, Y., Millo, G. et al. ( 2008 ). Panel data econometrics in R: The plm package, 27 ( 2 ), 1 â 43.
dc.identifier.citedreferenceDeng, S., Liu, L. & Zhao, X. ( 2015 ). Monotone splineâ based least squares estimation for panel count data with informative observation times. Biom. J., 57 ( 5 ), 743 â 765.
dc.identifier.citedreferenceElashoff, M. & Ryan, L. ( 2004 ). An EM algorithm for estimating equations. J. Comput. Graph. Statist., 13 ( 1 ), 48 â 65.
dc.identifier.citedreferenceGail, M.H., Santner, T.J. & Brown, C.C. ( 1980 ). An analysis of comparative carcinogenesis experiments based on multiple times to tumor. Biometrics, 36, 255 â 266.
dc.identifier.citedreferenceHe, X., Feng, X., Tong, X. & Zhao, X. ( 2017 ). Semiparametric partially linear varying coefficient models with panel count data. Lifetime Data Anal., 23 ( 3 ), 439 â 466.
dc.identifier.citedreferenceHe, X., Tong, X. & Sun, J. ( 2009 ). Semiparametric analysis of panel count data with correlated observation and followâ up times. Lifetime Data Anal., 15 ( 2 ), 177 â 196.
dc.identifier.citedreferenceHe, X., Tong, X., Sun, J. & Cook, R.J. ( 2008 ). Regression analysis of multivariate panel count data. Biostatistics, 9 ( 2 ), 234 â 248.
dc.identifier.citedreferenceHsiao, C. ( 2014 ). Analysis of Panel Data. Cambridge University Press: New York.
dc.identifier.citedreferenceHu, X.J., Lagakos, S.W. & Lockhart, R.A. ( 2009 ). Generalized least squares estimation of the mean function of a counting process based on panel counts. Statist. Sinica, 19, 561.
dc.identifier.citedreferenceHu, X.J., Lagakos, S.W. & Lockhart, R.A. ( 2009 ). Marginal analysis of panel counts through estimating functions. Biometrika, 96 ( 2 ), 445 â 456.
dc.identifier.citedreferenceHu, X., Sun, J. & Wei, L.â J. ( 2003 ). Regression parameter estimation from panel counts. Scand. J. Stat., 30 ( 1 ), 25 â 43.
dc.identifier.citedreferenceHua, L. & Zhang, Y. ( 2012 ). Splineâ based semiparametric projected generalized estimating equation method for panel count data. Biostatistics, 13 ( 3 ), 440 â 454.
dc.identifier.citedreferenceHua, L., Zhang, Y. & Tu, W. ( 2014 ). A splineâ based semiparametric sieve likelihood method for overâ dispersed panel count data. Canad. J. Statist., 42 ( 2 ), 217 â 245.
dc.identifier.citedreferenceHuang, C.â Y., Qin, J. & Wang, M.â C. ( 2010 ). Semiparametric analysis for recurrent event data with timeâ dependent covariates and informative censoring. Biometrics, 66 ( 1 ), 39 â 49.
dc.identifier.citedreferenceHuang, C.â Y., Wang, M.â C. & Zhang, Y. ( 2006 ). Analysing panel count data with informative observation times. Biometrika, 93 ( 4 ), 763 â 775.
dc.identifier.citedreferenceKalbfleisch, J. & Lawless, J.F. ( 1985 ). The analysis of panel data under a markov assumption. J. Amer. Statist. Assoc., 80 ( 392 ), 863 â 871.
dc.identifier.citedreferenceKalbfleisch, J.D. & Prentice, R.L. ( 2011 ). The statistical analysis of failure time data. John Wiley & Sons: New Jersey.
dc.identifier.citedreferenceKim, Y.â J. ( 2007 ). Analysis of panel count data with measurement errors in the covariates. J. Stat. Comput. Simul., 77 ( 2 ), 109 â 117.
dc.identifier.citedreferenceLa Cruz, W., Martínez, J. & Raydan, M. ( 2006 ). Spectral residual method without gradient information for solving largeâ scale nonlinear systems of equations. J. Stat. Comput. Simul., 75 ( 255 ), 1429 â 1448.
dc.identifier.citedreferenceLawless, J.F. & Nadeau, C. ( 1995 ). Some simple robust methods for the analysis of recurrent events. Technometrics, 37 ( 2 ), 158 â 168.
dc.identifier.citedreferenceLi, Y., He, X., Wang, H., Zhang, B. & Sun, J. ( 2015 ). Semiparametric regression of multivariate panel count data with informative observation times. J. Multivariate Anal., 140, 209 â 219.
dc.identifier.citedreferenceLi, N., Park, D.â H., Sun, J. & Kim, K. ( 2011 ). Semiparametric transformation models for multivariate panel count data with dependent observation process. Canad. J. Statist., 39 ( 3 ), 458 â 474.
dc.identifier.citedreferenceLi, N., Sun, L. & Sun, J. ( 2010 ). Semiparametric transformation models for panel count data with dependent observation process. Statistics in Biosciences, 2 ( 2 ), 191 â 210.
dc.identifier.citedreferenceLiang, K.â Y. & Zeger, S.L. ( 1986 ). Longitudinal data analysis using generalized linear models. Biometrika, 73, 13 â 22.
dc.identifier.citedreferenceLin, D., Wei, L., Yang, I. & Ying, Z. ( 2000 ). Semiparametric regression for the mean and rate functions of recurrent events. J. R. Stat. Soc. Ser. B, 62 ( 4 ), 711 â 730.
dc.identifier.citedreferenceLu, M., Zhang, Y. & Huang, J. ( 2009 ). Semiparametric estimation methods for panel count data using monotone bâ splines. J. Amer. Statist. Assoc., 104 ( 487 ), 1060 â 1070.
dc.identifier.citedreferenceMa, L. & Sundaram, R. ( 2018 ). Analysis of gap times based on panel count data with informative observation times and unknown start time. J. Amer. Statist. Assoc., 113 ( 521 ), 294 â 305.
dc.identifier.citedreferenceNelson, W. ( 1988 ). Graphical analysis of system repair data. Journal of Quality Technology, 20 ( 1 ), 24 â 35.
dc.identifier.citedreferencePepe, M.S. & Cai, J. ( 1993 ). Some graphical displays and marginal regression analyses for recurrent failure times and time dependent covariates. J. Amer. Statist. Assoc., 88 ( 423 ), 811 â 820.
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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