Leonora Pahirko, Janis Valeinis, Deivids Jēkabsons
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Two-sample empirical likelihood method for right censored data.
In this paper, a two-sample empirical likelihood method for right censored data is established. This method allows for comparisons between various functionals of survival distributions, such as mean lifetimes, survival probabilities at a fixed time, restricted mean survival times, and other parameters of interest. It is demonstrated that under some regularity conditions, the scaled empirical likelihood statistic converges to a chi-squared distributed random variable with one degree of freedom. A consistent estimator for the scaling constant is proposed, involving the jackknife estimator of the asymptotic variance of the Kaplan-Meier integral. A simulation study is carried out to investigate the coverage accuracy of confidence intervals. Finally, two real datasets are analyzed to illustrate the application of the proposed method.
期刊介绍:
The International Journal of Biostatistics (IJB) seeks to publish new biostatistical models and methods, new statistical theory, as well as original applications of statistical methods, for important practical problems arising from the biological, medical, public health, and agricultural sciences with an emphasis on semiparametric methods. Given many alternatives to publish exist within biostatistics, IJB offers a place to publish for research in biostatistics focusing on modern methods, often based on machine-learning and other data-adaptive methodologies, as well as providing a unique reading experience that compels the author to be explicit about the statistical inference problem addressed by the paper. IJB is intended that the journal cover the entire range of biostatistics, from theoretical advances to relevant and sensible translations of a practical problem into a statistical framework. Electronic publication also allows for data and software code to be appended, and opens the door for reproducible research allowing readers to easily replicate analyses described in a paper. Both original research and review articles will be warmly received, as will articles applying sound statistical methods to practical problems.