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Explains how statistical methods are used for data analysis and uses the elementary functions of R to perform the individual steps of statistical procedures. This title introduces basic concepts of inference through a study of several important procedures, including parametric and nonparametric methods, analysis of variance, and regression.

Covers both contemporary and classical aspects of statistics, including survival analysis, Kernel density estimation, Markov chain Monte Carlo, hypothesis testing, regression, bootstrap, and generalised linear models. This work provides the option of using powerful computational tools for stochastic modelling.

Covers a range of topics that include Poisson regression, survival analysis, repeated measure, clustered data, longitudinal observations, and generalized linear models such as logistic regression. This book explains the importance of time-dependent confounding and introduces methods including inverse probability weighted estimators.

Emphasizes basic methods for modeling linear dynamic systems. This book presents an understanding of basic concepts, such as multivariate random variables, stochastic processes, and regression-based methods. It covers topics that include spectral analysis, state space models, and recursive estimation.

Clinical trials have taken a prominent role in the research and approval of drugs. This text offers a summary of statistical design, including cross-over designs, sample size estimation, sequential methods for interim analyses, survival analysis, and repeated measures.

Incorporating changes in theory and highlighting various applications, this book presents a comprehensive introduction to the methods of Markov Chain Monte Carlo (MCMC) simulation technique. It incorporates the developments in MCMC, including reversible jump, slice sampling, bridge sampling, path sampling, multiple-try, and delayed rejection.

Reflects the developments in computer-intensive methods that deal with intractable analytical problems and unwieldy data sets. This title summarizes relevant general statistical concepts, introduces basic ideas of nonparametric or distribution-free methods, and features factorial treatment structures.

Focusing on the important role that statistical methods play in the analysis of the data collected as well as in the overall clinical trial process, this title provides an introduction to clinical trials. It features examples, exercises, and material on binary outcomes and survival analysis. It features various real examples taken from The Lancet.

Offers a comprehensive treatment of statistical theory and methods for spatial data analysis, employing a model-based and frequentist approach that emphasizes the spatial domain. This book delivers a treatment of semivariogram estimation and modeling, spatial analysis in the spectral domain, and spatial regression.

This classic textbook is suitable for a first course in the theory of statistics for students with a background in calculus, multivariate calculus, and the elements of matrix algebra.

A practical guide to statistical methods which reflects developments in the field. It includes a chapter introducing mixed models for binary data analysis and another on methods for modelling binary data. It also includes material on modelling ordered categorical data and provides a summary of the leading software packages.

Statistical ideas have been integral to the development of epidemiology and continue to provide the tools needed to interpret epidemiological studies. This title develops the techniques for analyzing simple risk factors and disease data. It covers the logistic regression model and contrasts it with the Cox model for time-to-incidence data.

"The book's simplicity of approach and clear presentation make it a good choice for an undergraduate course or a self-study course in multivariate analysis." -Journal of the American Statistical Association "The original aims of the book are fulfilled remarkably well, thus providing a text which is to be welcomed into an area where there has been a recent dearth of introductory material." -BIAS

Presents a set of useful tools that allow readers to understand the theoretical underpinnings of statistical methodology. This title emphasizes inferential procedures within the framework of parametric models.