Biostatistics R

Following a highly successful first edition, this book takes on a highly entertaining approach to an area normally reserved for dry, hard-to-follow books. Students benefit not only from the humorous aspects, but also from the in-depth and memorable discussions. This second edition features four new chapters on computer-intensive techniques, including MANOVA, Logistic Regression, Measuring Change and Structural Equation Modeling. This book is excellent for medical and other health professions students.

Competing Risks and Multistate Models with R covers models that generalize the analysis of time to a single event (survival analysis) to analyzing the timing of distinct terminal events (competing risks) and possible intermediate events (multistate models). Both R and multistate methods are promoted with a focus on non- and semiparametric methods.

The first seven chapters use R for probability simulation and computation, including random number generation, numerical and Monte Carlo integration, and finding limiting distributions of Markov Chains with both discrete and continuous states. Applications include coverage probabilities of binomial confidence intervals, estimation of disease prevalence from screening tests, parallel redundancy for improved reliability of systems, and various kinds of genetic modeling.

This unique volume provides self-contained accounts of some recent trends in Biostatistics methodology and their applications. It includes state-of-the-art reviews and original contributions.