Unconditional Uncensored
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Cure Models
Cure Models: Methods, Applications and Implementation is the first book in the last 25 years that provides a comprehensive and systematic introduction to the basics of modern cure models, including estimation, inference, and software. This book is useful for statistical researchers and graduate students, and practitioners in other disciplines to have a thorough review of modern cure model methodology and to seek appropriate cure models in applications. The prerequisites of this book include some basic knowledge of statistical modeling, survival models, and R and SAS for data analysis. The book features real-world examples from clinical trials and population-based studies and a detailed introduction to R packages, SAS macros, and WinBUGS programs to fit some cure models. The main topics covered include the foundation of statistical estimation and inference of cure models for independent and right-censored survival data, cure modeling for multivariate, recurrent-event, and competing-risks survival data, and joint modeling with longitudinal data, statistical testing for the existence and difference of cure rates and sufficient follow-up, new developments in Bayesian cure models, applications of cure models in public health research and clinical trials.
Advanced Play Therapy
The purpose of this text is to present a resource to students and practitioners of play therapy that addresses topics beyond the training level. It provides advanced knowledge on the three main areas of play, child development, and play therapy and integrates them to help the play therapist gain a holistic understanding of how play therapy works.
A Comparison of Alternative Models for the Demand for Medical Care
This report evaluates alternative statistical models of the demand for medical care. The report discusses the estimation problems, the alternative models considered, and the choice of a final model. Chapter 2 briefly describes the design of the Health Insurance Study, which is the source of the data, and the sample. Chapter 3 provides a rationale for and description of each of the models considered, and Chap. 4 indicates the sensitivity of the empirical results to the estimation model. Chapter 5 compares the models empirically in terms of forecast bias and mean squared forecast error, using a split-sample technique. Chapter 6 summarizes the findings of this study.