Modelling and analysis of recall-based competing risks data

ABSTRACT In this paper we consider the analysis of recall-based competing risks data. The chance of an individual recalling the exact time to event depends on the time of occurrence of the event and time of observation of the individual. In particular, it is assumed that the probability of recall depends on the time elapsed since the occurrence of an event. In this study we consider the likelihood-based inference for the analysis of recall-based competing risks data. The likelihood function is constructed by incorporating the information about the probability of recall. We consider the maximum likelihood estimation of parameters. Simulation studies are carried out to examine the performance of the estimators. The proposed estimation procedure is applied to a real life data set.

[1]  Gordon Johnston,et al.  Statistical Models and Methods for Lifetime Data , 2003, Technometrics.

[2]  Gregg E. Dinse,et al.  A mixture model for the regression analysis of competing risks data , 1985 .

[3]  Debasis Sengupta,et al.  Regression under Cox's model for recall-based time-to-event data in observational studies , 2015, Comput. Stat. Data Anal..

[4]  Jason P Fine,et al.  Parametric likelihood inference for interval censored competing risks data. , 2014, Biometrics.

[5]  Xuewen Lu,et al.  Partially linear single-index proportional hazards model with current status data , 2016, J. Multivar. Anal..

[6]  Xian Zhou,et al.  Analysis of parametric models for competing risks , 2002 .

[7]  P. X. Song,et al.  Efficient Estimation of the Partly Linear Additive Hazards Model with Current Status Data , 2015 .

[8]  R. Betensky Miscellanea. On nonidentifiability and noninformative censoring for current status data , 2000 .

[9]  Debasis Sengupta,et al.  Nonparametric estimation of time-to-event distribution based on recall data in observational studies , 2015, Lifetime Data Analysis.

[10]  T. Nakamura Existence of Maximum Likelihood Estimates for Interval-censored Data from Some Three-parameter Models with a Shifted Origin , 1991 .

[11]  Alicia Worrall,et al.  Statistical analysis of interval-censored failure time data , 2015 .

[12]  J. Fine,et al.  Parametric regression on cumulative incidence function. , 2007, Biostatistics.

[13]  Debasis Sengupta,et al.  Parametric Estimation of Menarcheal Age Distribution Based on Recall Data , 2015 .

[14]  Nicholas P. Jewell,et al.  Nonparametric estimation from current status data with competing risks , 2003 .

[15]  Marloes H. Maathuis,et al.  Nonparametric estimation for current status data with competing risks , 2007 .

[16]  David B Dunson,et al.  Bayesian Models for Multivariate Current Status Data with Informative Censoring , 2002, Biometrics.

[17]  M. Hediger,et al.  Age at menarche based on recall information. , 1987, Annals of human biology.

[18]  Jianguo Sun,et al.  The Statistical Analysis of Interval-censored Failure Time Data , 2006 .

[19]  Jianguo Sun,et al.  Nonparametric Treatment Comparison for Current Status Data , 2010 .

[20]  Richard J. Cook,et al.  The Statistical Analysis of Recurrent Events , 2007 .