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区间删失复发事件数据混合效应模型
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  • 英文篇名:The Mixed Effects Model Based on Interval Censored Recurrent Event Data
  • 作者:李俊琳 ; 吕成余 ; 李霓
  • 英文作者:LI Junlin;Lü Chengyu;LI Ni;School of Mathematics and Statistics,Hainan Normal University;Nanjing First Hospital;
  • 关键词:混合效应模型 ; 协变量 ; 极大似然估计 ; 区间删失复发事件数据
  • 英文关键词:mixed effects model;;covariate;;maximum likelihood estimation;;interval censored recurrent event data
  • 中文刊名:HNXZ
  • 英文刊名:Journal of Hainan Normal University(Natural Science)
  • 机构:海南师范大学数学与统计学院;南京市第一医院;
  • 出版日期:2019-06-15
  • 出版单位:海南师范大学学报(自然科学版)
  • 年:2019
  • 期:v.32
  • 基金:国家自然科学基金项目(11861030,11471135)
  • 语种:中文;
  • 页:HNXZ201902013
  • 页数:12
  • CN:02
  • ISSN:46-1075/N
  • 分类号:66-77
摘要
通过向一般速率模型中引入随机效应项来研究区间删失复发事件数据的个体异质性,允许协变量对含有区间删失的复发事件数据产生影响。在给定随机因子和协变量的条件下建立基于区间删失复发事件数据的混合效应模型。利用极大似然方法估计此模型中所感兴趣的参数,证明此混合效应模型中参数估计的相合性与渐近正态性。通过大量的数值模拟试验研究混合效应模型和参数估计方法的有限样本性质,对一组真实膀胱癌数据的分析表明服用三胺硫磷可以降低膀胱癌的复发率。
        In this paper, the random effect item was incorporated into the general rate model to deal with the individual heterogeneity of interval censored recurrent event data, and allowed covariates to affect interval censored recurrent event data, and a mixed effect model was proposed by given random factors and covariates. The model parameters were estimated under the maximum likelihood procedures, the large sample properties in terms of consistency and asymptotic normality properties of the proposed estimates. The finite sample properties of the mixed effects model and the parameters estimate method in this paper were investigated by a large number of numerical simulation experiments. An illustrative example from a bladder cancer study was provided to indicate that the rate of bladder cancer could reduce by taking thiotepa.
引文
[1] KALBFLEISCH J D,LAWLESS J F. The analysis of panel data under a Markov assumption[J]. Journal of the American Statistical Association,1985,80(392):863-871.
    [2] SUN J. The statistical analysis of interval-censored failure time data[M]. New York:Springer,2006.
    [3] SUN J,ZHAO X. Statistical analysis of panel count data[M]. New York:Springer,2013.
    [4] SUN J,WEI L J. Regression analysis of panel count data with covariate-dependent observation and censoring times[J]. Journal ofthe Royal Statistical Society,2000,62(2):293-302.
    [5] SUN J,KALBFLEISCH J D. Estimation of the mean function of point processes based on panel data[J]. Statistica Sinica,1995,5(1):279-289.
    [6] BALAKRISHNAN N,ZHAO X. New multi-sample nonparametric tests for panel count data[J]. Annals of Statistics,2009,37(3):1112-1149.
    [7] BALAKRISHNAN N,ZHAO X. A nonparametric tests for the equality of counting processes with panel count data[J]. Computation-al Statistics and Data Analysis,2010,54(1):135-142.
    [8] BALAKRISHNAN N,ZHAO X. A class of multi-sample nonparametric tests for panel count data[J]. Annals of the Institute of Sta-tistical Mathematics,2011,63(1):135-156.
    [9] PARK D,SUN J,ZHAO X. A class of two-sample nonparametric tests for panel count data[J]. Communications in Statistics-Theo-ry and Methods,2007,36(8):1611-1625.
    [10] SUN J,FANG H. A nonparametric test for panel count data[J]. Biometrika,2003,90(1):199-208.
    [11] ZHAO X,SUN J. Nonparametric comparison for panel count data with unequal observation processes[J]. Biometrics,2011,67(3):770-779.
    [12] HU X J,SUN J,WEI L J. Regression parameter estimation from panel counts[J]. Scandinavian Journal of Statistics,2003,30(1):25-43.
    [13] SUN J,ZHAO X. Statistical analysis of panel count data[M]. New York:Springer,2013.
    [14] SHAO J. Mathematical statistics[M]. Second edition. New York:Springer-Verlag,2003.
    [15]周勇.广义估计方程估计方法[M].北京:科学出版社,2013.
    [16]陈希孺.数理统计引论[M].北京:科学出版社,1997.
    [17] ZHU L,ZHAO H,SUN J,et al. Regression analysis of mixed recurrent-event and panel-count data with additive rate models[J].Biometrics,2015,71(1):71-79.

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