BOOK SERIES


Chapman & Hall/CRC Monographs on Statistics & Applied Probability


125 Series Titles

Per Page
Sort

Display
Nonparametric Models for Longitudinal Data: With Implementation in R

Nonparametric Models for Longitudinal Data: With Implementation in R

Forthcoming

Colin O. Wu, Xin Tian
July 15, 2017

This book covers the recent advancement of statistical methods for the analysis of longitudinal data. Real datasets from four large NIH-supported longitudinal clinical trials and epidemiological studies illustrate the practical applications of the statistical methods. This book focuses on the...

The Statistical Analysis of Multivariate Time

The Statistical Analysis of Multivariate Time

Forthcoming

Ross L. Prentice, Shanshan Zhao
July 15, 2017

Though much has been written on multivariate failure time data analysis methods, a unified approach to this topic has yet to be communicated. This book aims to fill that gap through a novel focus on marginal hazard rates and cross ratio modeling. Readers will find the content useful for instruction...

Multistate Models for the Analysis of Life History Data

Multistate Models for the Analysis of Life History Data

Forthcoming

Richard J Cook, Jerald F. Lawless
July 15, 2017

Martingale Methods in Statistics

Martingale Methods in Statistics

Forthcoming

Yoichi Nishiyama
July 01, 2017

This gives a comprehensive introduction to the (standard) statistical analysis based on the theory of martingales and develops entropy methods in order to treat dependent data in the framework of martingales. The author starts a summary of the martingale theory, and then proceeds to give full...

Handbook of Approximate Bayesian Computation

Handbook of Approximate Bayesian Computation

Forthcoming

Scott A. Sisson, Yanan Fan, Mark Beaumont
June 15, 2017

Approximate Bayesian Computation (ABC) methods, also known as "likelihood-free" inference methods, can be used to solve very complex ("computationally intractable") problems. A huge amount of research has been conducted in this area over the last decade and a varied suite of algorithms, models,...

Mixed Effects Model Asymptotics

Mixed Effects Model Asymptotics

Forthcoming

Jiming Jiang
May 15, 2017

Mixed effects models, including linear mixed models, generalized linear mixed models, nonlinear mixed effects models, and non-parametric mixed effects models, are complex models by nature; yet, these models are extensively used in practice. This monograph provides a comprehensive overview of...

Absolute or Crude Risk: Methods and Applications in Disease Prevention

Absolute or Crude Risk: Methods and Applications in Disease Prevention

Forthcoming

Ruth Pfeiffer, Mitchell H. Gail
April 01, 2017

Absolute risk is the probability of developing a specific disease over a specified time interval in the presence of competing causes of mortality. Although absolute risk is arguably more relevant to clinical decision making than "pure" risk, the development of appropriate statistical methods for...

Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood, Second Edition

Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood, Second Edition

Forthcoming

Youngjo Lee, John A. Nelder, Yudi Pawitan
December 19, 2016

This is the second edition of a monograph on generalized linear models with random effects that extends the classic work of McCullagh and Nelder. It has been thoroughly updated, with around 80 pages added, including new material on the extended likelihood approach that strengthens the theoretical...

Multi-State Survival Models for Interval-Censored Data

Multi-State Survival Models for Interval-Censored Data

Ardo van den Hout
September 29, 2016

Multi-State Survival Models for Interval-Censored Data introduces methods to describe stochastic processes that consist of transitions between states over time. It is targeted at researchers in medical statistics, epidemiology, demography, and social statistics. One of the applications in the book...

Joint Modeling of Longitudinal and Time-to-Event Data

Joint Modeling of Longitudinal and Time-to-Event Data

Robert Elashoff, Gang li, Ning Li
August 24, 2016

Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable missing data in longitudinal measurements of one or more response variables, informative observation times of longitudinal data, and survival...

Hidden Markov Models for Time Series: An Introduction Using R, Second Edition

Hidden Markov Models for Time Series: An Introduction Using R, Second Edition

Walter Zucchini, Iain L. MacDonald, Roland Langrock
August 17, 2016

Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their uses. After presenting the basic model...

AJAX loader