Dr. Jong-Hyeon Jeong is a full professor of Biostatistics at the University of Pittsburgh. Dr. Jeong's main research area has been survival analysis and clinical trials. In survival analysis, he has worked on frailty modeling, efficiency of survival probability estimates from the proportional hazards model, weighted log-rank test, competing risks, quantile residual life, and likelihood theory such as empirical likelihood and hierarchical likelihood. In clinical trials, he has been involved in several phase III clinical trials on breast cancer treatment as the primary statistician. He has been teaching statistical theory courses and survival analysis in the Department of Biostatistics at the University of Pittsburgh. Dr. Jeong holds his PhD degree in statistics from the University of Rochester and has been an elected member of the International Statistical Institute (ISI) since 2007.

"It is the very first book in its kind that is entirely devoted to the statistical methodologies aimed to analyze residual life and related quantities. ... would be a must-have item for researchers who are interested in learning statistical theory on the quantile residual life functions. ... would be a valuable asset to those who work on survival analysis. It would be beneficial to a wide group of audience who are interested in the analysis of quantile residual functions." (Sangwook Kang, Journal of Agricultural, Biological, and Environmental Statistics, Vol. 20, 2015) "This book on the statistical analysis of life expectancy focuses on history, research achievements, and recent developments in statistical inference on quantile residual lifetime. ... The intended audience includes graduate students and researchers both in academia and in industry who are interested in learning the theory and application of the residual life function. ... This book is strongly recommended to beginning researchers and statistician who are interested in learning the theory and application of the residual life function." (Samit Bhatheja, Doody's Book Reviews, May, 2014)

• Introduction.- Inference on Mean Residual Life.- Quantile Residual Life.- Quantile Residual Life under Competing Risks.- Other Methods for Inference on Quantiles.- Study Design based on Quantile (Residual) Life.- Appendix: R codes.- References.- Index.

Dr. Jong-Hyeon Jeong is a full professor of Biostatistics at the University of Pittsburgh. Dr. Jeong's main research area has been survival analysis and clinical trials. In survival analysis, he has worked on frailty modeling, efficiency of survival probability estimates from the proportional hazards model, weighted log-rank test, competing risks, quantile residual life, and likelihood theory such as empirical likelihood and hierarchical likelihood. In clinical trials, he has been involved in several phase III clinical trials on breast cancer treatment as the primary statistician. He has been teaching statistical theory courses and survival analysis in the Department of Biostatistics at the University of Pittsburgh. Dr. Jeong holds his PhD degree in statistics from the University of Rochester and has been an elected member of the International Statistical Institute (ISI) since 2007.

"It is the very first book in its kind that is entirely devoted to the statistical methodologies aimed to analyze residual life and related quantities. ... would be a must-have item for researchers who are interested in learning statistical theory on the quantile residual life functions. ... would be a valuable asset to those who work on survival analysis. It would be beneficial to a wide group of audience who are interested in the analysis of quantile residual functions." (Sangwook Kang, Journal of Agricultural, Biological, and Environmental Statistics, Vol. 20, 2015) "This book on the statistical analysis of life expectancy focuses on history, research achievements, and recent developments in statistical inference on quantile residual lifetime. ... The intended audience includes graduate students and researchers both in academia and in industry who are interested in learning the theory and application of the residual life function. ... This book is strongly recommended to beginning researchers and statistician who are interested in learning the theory and application of the residual life function." (Samit Bhatheja, Doody's Book Reviews, May, 2014)

• Introduction.- Inference on Mean Residual Life.- Quantile Residual Life.- Quantile Residual Life under Competing Risks.- Other Methods for Inference on Quantiles.- Study Design based on Quantile (Residual) Life.- Appendix: R codes.- References.- Index.