New and Published Books
1-10 of 32 results in Chapman & Hall/CRC Interdisciplinary Statistics
Methods for Using Genetic Variants in Causal Estimation
Presents the Terminology and Methods of Mendelian Randomization for Epidemiological Studies Mendelian randomization uses genetic instrumental variables to make inferences about causal effects based on observational data. It, therefore, can be a reliable way of assessing the causal nature of risk...
Published March 6th 2015 by Chapman and Hall/CRC
An important first step in studying the demography of wild animals is to identify the animals uniquely through applying markings, such as rings, tags, and bands. Once the animals are encountered again, researchers can study different forms of capture-recapture data to estimate features, such as the...
Published August 1st 2014 by Chapman and Hall/CRC
Hierarchical Modeling in Spatial Epidemiology, Second Edition
Since the publication of the first edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas. Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in...
Published March 18th 2013 by Chapman and Hall/CRC
New Models, Methods, and Empirical Applications
Age-Period-Cohort Analysis: New Models, Methods, and Empirical Applications is based on a decade of the authors’ collaborative work in age-period-cohort (APC) analysis. Within a single, consistent HAPC-GLMM statistical modeling framework, the authors synthesize APC models and methods for three...
Published February 25th 2013 by Chapman and Hall/CRC
The third edition of the bestselling Clinical Trials in Oncology provides a concise, nontechnical, and thoroughly up-to-date review of methods and issues related to cancer clinical trials. The authors emphasize the importance of proper study design, analysis, and data management and identify the...
Published May 9th 2012 by CRC Press
Missing data form a problem in every scientific discipline, yet the techniques required to handle them are complicated and often lacking. One of the great ideas in statistical science—multiple imputation—fills gaps in the data with plausible values, the uncertainty of which is coded in the data...
Published March 29th 2012 by Chapman and Hall/CRC
Recent advances in brain science measurement technology have given researchers access to very large-scale time series data such as EEG/MEG data (20 to 100 dimensional) and fMRI (140,000 dimensional) data. To analyze such massive data, efficient computational and statistical methods are required....
Published January 26th 2012 by CRC Press
Statistical investigation into technology not only provides a better understanding of the intrinsic features of the technology (analysis), but also leads to an improved design of the technology (synthesis). Physical principles and mathematical procedures of medical imaging technologies have been...
Published December 19th 2011 by Chapman and Hall/CRC
Theory and Applications
Generalized Linear Models: Theory and Applications provides a comprehensive, practical introduction to generalized linear models that covers all of the main models and methods of estimation. Worked examples of real data are backed up by implementation in a range of software packages, including R,...
Published June 15th 2010 by Chapman and Hall/CRC
After more than 15 years of development drawing on research in cognitive psychology, statistical graphics, computer science, and cartography, micromap designs are becoming part of mainstream statistical visualizations. Bringing together the research of two leaders in this field, Visualizing Data...
Published April 29th 2010 by Chapman and Hall/CRC
Power Analysis of Trials with Multilevel Data
To Be Published July 27th 2015
Statistical Analysis of Questionnaires: A Unified Approach Based on R and Stata
To Be Published August 5th 2015
Missing Data Analysis in Practice
To Be Published October 19th 2015
Spatial Point Patterns: Methodology and Applications with R
To Be Published November 25th 2015
Statistics for Biological Networks: How to Infer Networks from Data
To Be Published June 15th 2016