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Annals of Data Science

19-03-2024

Semiparametric Regression Analysis of Panel Count Data with Multiple Modes of Recurrence

Authors: Mathew P. M. Ashlin, P. G. Sankaran, E. P. Sreedevi

Published in: Annals of Data Science

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Abstract

Panel count data refers to the information collected in studies focusing on recurrent events, where subjects are observed only at specific time points. If these study subjects are exposed to recurrent events of several types, we obtain panel count data with multiple modes of recurrence. In this article, we present a novel method based on generalized estimating equations for the regression analysis of panel count data exposed to multiple modes of recurrence. A cause specific proportional mean model is developed to analyze the effect of covariates on the underlying counting process due to multiple modes of recurrence. We conduct a detailed investigation on the joint estimation of baseline cumulative mean functions and regression parameters. Simulation studies are carried out to evaluate the finite sample performance of the proposed estimators. The procedures are applied to two real data sets, to demonstrate the practical utility.

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Kalbfleisch JD, Lawless JF (1985) The analysis of panel data under a markov assumption. J Am Stat Assoc 80(392):863–871. https://doi.org/10.1080/01621459.1985.10478195MathSciNetCrossRef

Sun L, Tong X (2009) Analyzing longitudinal data with informative observation times under biased sampling. Stat Probab Lett 79(9):1162–1168. https://doi.org/10.1016/j.spl.2008.12.022MathSciNetCrossRef

Lawless JF, Zhan M (1998) Analysis of interval-grouped recurrent-event data using piecewise constant rate functions. Can J Stat 26(4):549–565. https://doi.org/10.2307/3315717CrossRef

Thall PF, Lachin JM (1988) Analysis of recurrent events: Nonparametric methods for random-interval count data. J Am Stat Assoc 83(402):339–347. https://doi.org/10.1080/01621459.1988.10478603CrossRef

Steele AJ, Denaxas SC, Shah AD, Anoop D, Hemingway H, Luscombe NM (2018) Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease. PloS One 13(8):e0202344. https://doi.org/10.1371/journal.pone.0202344CrossRefPubMedPubMedCentral

Spooner A, Chen E, Sowmya A, Sachdev P, Kochan NA, Trollor J, Brodaty H (2020) A comparison of machine learning methods for survival analysis of high-dimensional clinical data for dementia prediction. Sci Rep 10(1):20410. https://doi.org/10.1038/s41598-020-77220-wCrossRefPubMedPubMedCentral

Huang Y, Li J, Li M, Aparasu RR (2023) Application of machine learning in predicting survival outcomes involving real-world data: a scoping review. BMC Medical Res Methodol 23(1):1–11. https://doi.org/10.1186/s12874-023-02078-1CrossRef

Olson DL, Shi Y (2007) Introduction to business data mining. McGraw-Hill/Irwin, New York

Shi Y, Tian Y, Kou G, Peng Y, Li J (2011) Optimization based data mining: theory and applications. Springer, Berlin. https://doi.org/10.1007/978-0-85729-504-0CrossRef

10.

Tien JM (2017) Internet of things, real-time decision making, and artificial intelligence. Ann Data Sci 4(2):149–178. https://doi.org/10.1007/s40745-017-0112-5CrossRef

11.

Shi Y (2022) Advances in big data analytics: theory, algorithms and practices. Springer, Singapore. https://doi.org/10.1007/978-981-16-3607-3CrossRef

12.

Sun J, Kalbfleisch J (1995) Estimation of the mean function of point processes based on panel count data. Stat Sin 5(1):279–289MathSciNet

13.

Wellner JA, Zhang Y (2000) Two estimators of the mean of a counting process with panel count data. Ann Stat 28(3):779–814MathSciNetCrossRef

14.

Zhou J, Zhang H, Sun L, Sun J (2017) Joint analysis of panel count data with an informative observation process and a dependent terminal event. Lifetime Data Anal 23(4):560–584. https://doi.org/10.1007/s10985-016-9375-yMathSciNetCrossRefPubMed

15.

Xu D, Zhao H, Sun J (2018) Joint analysis of interval-censored failure time data and panel count data. Lifetime Data Anal 24(1):94–109. https://doi.org/10.1007/s10985-017-9397-0MathSciNetCrossRefPubMed

16.

Wang W, Wu X, Zhao X, Zhou X (2019) Quantile estimation of partially varying coefficient model for panel count data with informative observation times. J Nonparametr Stat 31(4):932–951. https://doi.org/10.1080/10485252.2019.1666128MathSciNetCrossRef

17.

Jiang H, Su W, Zhao X (2020) Robust estimation for panel count data with informative observation times and censoring times. Lifetime Data Anal 26(1):65–84. https://doi.org/10.1007/s10985-018-09457-7MathSciNetCrossRefPubMed

18.

Wang J, Lin X (2020) A bayesian approach for semiparametric regression analysis of panel count data. Lifetime Data Anal 26(2):402–420. https://doi.org/10.1007/s10985-019-09471-3MathSciNetCrossRefPubMed

19.

Zhang Y (2002) A semiparametric pseudolikelihood estimation method for panel count data. Biometrika 89(1):39–48. https://doi.org/10.1093/biomet/89.1.39MathSciNetCrossRef

20.

Wellner JA, Zhang Y (2007) Two likelihood-based semiparametric estimation methods for panel count data with covariates. Ann Stat 35(5):2106–2142. https://doi.org/10.1214/009053607000000181MathSciNetCrossRef

21.

Hu XJ, Sun J, Wei LJ (2003) Regression parameter estimation from panel counts. Scand Stat Theory Appl 30(1):25–43. https://doi.org/10.1111/1467-9469.00316MathSciNetCrossRef

22.

Sun J, Wei L (2000) Regression analysis of panel count data with covariate-dependent observation and censoring times. J R Stat Soc, Ser B, Methodol 62(2):293–302. https://doi.org/10.1111/1467-9868.00232MathSciNetCrossRef

23.

Huang CY, Wang MC, Zhang Y (2006) Analysing panel count data with informative observation times. Biometrika 93(4):763–775. https://doi.org/10.1093/biomet/93.4.763MathSciNetCrossRefPubMed

24.

Sun J, Tong X, He X (2007) Regression analysis of panel count data with dependent observation times. Biometrics 63(4):1053–1059. https://doi.org/10.1111/j.1541-0420.2007.00808.xMathSciNetCrossRefPubMed

25.

Zhao X, Tong X (2011) Semiparametric regression analysis of panel count data with informative observation times. Comput Stat Data Anal 55(1):291–300. https://doi.org/10.1016/j.csda.2010.04.020MathSciNetCrossRef

26.

He X, Tong X, Sun J (2009) Semiparametric analysis of panel count data with correlated observation and follow-up times. Lifetime Data Anal 15(2):177–196. https://doi.org/10.1007/s10985-008-9105-1MathSciNetCrossRefPubMed

27.

Yao B, Wang L, He X (2016) Semiparametric regression analysis of panel count data allowing for within-subject correlation. Comput Stat Data Anal 100(97):47–59. https://doi.org/10.1016/j.csda.2015.11.017MathSciNetCrossRef

28.

Zhao H, Zhang Y, Zhao X, Yu Z (2019) A nonparametric regression model for panel count data analysis. Stat Sin 29(2):809–826MathSciNet

29.

He X, Tong X, Sun J, Cook RJ (2008) Regression analysis of multivariate panel count data. Biostatistics 9(2):234–248. https://doi.org/10.1093/biostatistics/kxm025CrossRefPubMed

30.

Zhang H, Zhao H, Sun J, Wang D, Kim K (2013) Regression analysis of multivariate panel count data with an informative observation process. J Multivar Anal 119(C):71–80. https://doi.org/10.1016/j.jmva.2013.04.012MathSciNetCrossRef

31.

Chiou SH, Huang CY, Xu G, Yan J (2019) Semiparametric regression analysis of panel count data: a practical review. Int Stat Rev 87(1):24–43. https://doi.org/10.1111/insr.12271MathSciNetCrossRefPubMed

32.

Sun J, Zhao X (2013) Statistical analysis of panel count data. Springer, New York. https://doi.org/10.1007/978-1-4614-8715-9CrossRef

33.

Sankaran PG, Ashlin-Mathew PM, Sreedevi EP (2020) Cause specific rate functions for panel count data with multiple modes of recurrence. J Indian Stat Assoc 58(2):193–211MathSciNet

34.

Sreedevi EP, Sankaran PG (2021) Nonparametric inference for panel count data with competing risks. J Appl Stat 48(16):3102–3115. https://doi.org/10.1080/02664763.2020.1795816MathSciNetCrossRefPubMed

35.

Lawless JF, Nadeau C (1995) Some simple robust methods for the analysis of recurrent events. Technometrics 37(2):158–168. https://doi.org/10.1080/00401706.1995.10484300MathSciNetCrossRef

36.

Crowder MJ (2012) Multivariate survival analysis and competing risks. CRC Press, Boca Raton, FloridaCrossRef

37.

Andersen PK, Gill RD (1982) Cox’s regression model for counting processes: a large sample study. Ann Stat 10(4):1100–1120MathSciNetCrossRef

38.

Klein JP, Moeschberger ML (2003) Survival analysis: techniques for censored and truncated data. Springer, New York. https://doi.org/10.1007/b97377CrossRef

39.

Sankaran PG, Sreedevi EP (2016) A proportional hazards model for the analysis of doubly censored competing risks data. Commun Stat Theory Methods 45(10):2975–2987. https://doi.org/10.1080/03610926.2014.894064MathSciNetCrossRef

40.

Bilias Y, Gu M, Ying Z (1997) Towards a general asymptotic theory for cox model with staggered entry. Ann Stat 25(2):662–682. https://doi.org/10.1214/aos/1031833668MathSciNetCrossRef

41.

Pollard D (1990) Empirical processes: theory and applications. In NSF-CBMS Regional Conference Series in Probability and Statistics 2. Institute of Mathematical Statistics, Hayward, CA

42.

Shorack GR, Wellner JA (1986) Empirical Processes with Applications to Statistics. Wiley Series in Probability and Mathematical Statistics, Wiley, New York

Title: Semiparametric Regression Analysis of Panel Count Data with Multiple Modes of Recurrence
Authors: Mathew P. M. Ashlin
P. G. Sankaran
E. P. Sreedevi
Publication date: 19-03-2024
Publisher: Springer Berlin Heidelberg
Published in: Annals of Data Science
Print ISSN: 2198-5804
Electronic ISSN: 2198-5812
DOI: https://doi.org/10.1007/s40745-024-00522-7

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