General

Randomization, Masking, and Allocation Concealment is indispensable for any trial researcher who wants to use state of the art randomization methods, and also wants to be able to describe these methods correctly.Far too often the subtle nuances that...

This book collects important advances in methodology and data analysis for directional statistics. It is the companion book of the more theoretical treatment presented in Modern Directional Statistics (CRC Press, 2017). The field of directional...

Circulant matrices have been around for a long time and have been extensively used in many scientific areas. This book studies the properties of the eigenvalues for various types of circulant matrices, such as the usual circulant, the reverse circulant,...

This book focuses on analytical similarity assessment in biosimilar product development following the FDA's recommended stepwise approach for obtaining totality-of-the-evidence for approval of biosimilar products. It covers concepts such as the tiered...

Cost-effectiveness analysis is becoming an increasingly important tool for decision making in the health systems. Cost-Effectiveness of Medical Treatments formulates the cost-effectiveness analysis as a statistical decision problem, identifies the...

Of the two primary approaches to the classic source separation problem, only one does not impose potentially unreasonable model and likelihood constraints: the Bayesian statistical approach. Bayesian methods incorporate the available information...

Response Surfaces: Designs and Analyses; Second Edition presents techniques for designing experiments that yield adequate and reliable measurements of one or several responses of interest, fitting and testing the suitability of empirical models used for...

Bayesian methods in reliability cannot be fully utilized and understood without full comprehension of the essential differences that exist between frequentist probability and subjective probability. Switching from the frequentist to the subjective...

A technically precise yet clear presentation of modern sequential methodologies having immediate applications to practical problems in the real world, Applied Sequential Methodologies communicates invaluable techniques for data mining, agricultural...

Statistical analyses of the numbers, lengths, and orientations of fission tracks etched in minerals yield dating and thermal history information valuable in geological and geoscience applications, particularly in oil exploration. Fission tracks can be...

Quantification of categorical, or non-numerical, data is a problem that scientists face across a wide range of disciplines. Exploring data analysis in various areas of research, such as the social sciences and biology, Multidimensional Nonlinear...

Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention in the economics and statistics communities over the past twenty years. Recent studies show that semiparametric...

Bayesian analyses have made important inroads in modern clinical research due, in part, to the incorporation of the traditional tools of noninformative priors as well as the modern innovations of adaptive randomization and predictive power. Presenting an...

Continuing advances in biomedical research and statistical methods call for a constant stream of updated, cohesive accounts of new developments so that the methodologies can be properly implemented in the biomedical field. Responding to this need,...

Providing reliable information on an intervention effect, meta-analysis is a powerful statistical tool for analyzing and combining results from individual studies. Meta-Analysis of Binary Data Using Profile Likelihood focuses on the analysis and modeling...

Due to the tremendous accumulation of data for genetic markers, pharmacogenomics, the study of the functions and interactions of all genes in the overall variability of drug response, is one of the hottest areas of research in biomedical science...

Examines Critical Decisions for Transitioning Lab Science to a Clinical SettingThe development of therapeutic pharmaceutical compounds is becoming more expensive, and the success rates for getting such treatments approved for marketing and to the...

Bayesian Missing Data Problems: EM, Data Augmentation and Noniterative Computation presents solutions to missing data problems through explicit or noniterative sampling calculation of Bayesian posteriors. The methods are based on the inverse Bayes...

Effectively Assess Intervention Options for Controlling Infectious DiseasesOur experiences with the human immunodeficiency virus (HIV), severe acute respiratory syndrome (SARS), and Ebola virus disease (EVD) remind us of the continuing need to be...

All the Essentials to Start Using Adaptive Designs in No TimeCompared to traditional clinical trial designs, adaptive designs often lead to increased success rates in drug development at reduced costs and time. Introductory Adaptive Trial Designs: A...

Sharpening Your Advanced SAS (R) Skills presents sophisticated SAS programming techniques, procedures, and tools, such as Proc SQL, hash tables, and SAS Macro programming, for any industry. Drawing on his more than 20 years' experience of SAS programming...

Covering both theory and applications, this collection of eleven contributed papers surveys the role of probabilistic models and statistical techniques in image analysis and processing, develops likelihood methods for inference about parameters that...

Praise for the First Edition ". . . an excellent textbook . . . an indispensable reference for biostatisticians and epidemiologists." -International Statistical Institute A new edition of the definitive guide to classical and modern methods of...

Now in its fourth edition, Behavioral Research and Analysis: An Introduction to Statistics within the Context of Experimental Design presents an overview of statistical methods within the context of experimental design. It covers fundamental topics such...

This book sheds new light on stochastic calculus, the branch of mathematics that is most widely applied in financial engineering and mathematical finance. The first book to introduce pathwise formulae for the stochastic integral, it provides a simple but...

Interest in predictive analytics of big data has grown exponentially in the four years since the publication of Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition. In the third...

An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demonstrates the advantages of a Bayesian approach to data sets involving inferences for collections of related units or variables, and in methods where...

Review of the First Edition"The goal of this book, as stated by the authors, is to fill the knowledge gap that exists between developed statistical methods and the applications of these methods. Overall, this book achieves the goal successfully and does...

Newcomers to R are often intimidated by the command-line interface, the vast number of functions and packages, or the processes of importing data and performing a simple statistical analysis. The R Primer provides a collection of concise examples and...

Mixture Modelling for Medical and Health Sciences provides a direct connection between theoretical developments in mixture modelling and their applications in real world problems. The book describes the development of the most important concepts through...

Winner of the 2015 Sugiyama Meiko Award (Publication Award) of the Behaviormetric Society of JapanDeveloped by the authors, generalized structured component analysis is an alternative to two longstanding approaches to structural equation modeling:...

This text introduces engineering students to probability theory and stochastic processes. Along with thorough mathematical development of the subject, the book presents intuitive explanations of key points in order to give students the insights they need...

This book surveys what executives who make decisions based on forecasts and professionals responsible for forecasts should know about forecasting. It discusses how individuals and firms should think about forecasting and guidelines for good practices. It...

This book provides a thorough understanding of distribution theory and data analysis using statistical software to solve problems related to basic statistics, probability models, and simulation. It presents a detailed explanation of different...

At the interface between chemistry, biology, and physics, fullerenes were one of the first objects to be dissected, scanned, and studied by the modern multi-specialty biotech community and are currently thriving in both research and practical application...

Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers...

Now ubiquitous in modern life, spatial data present great opportunities to transform many of the processes on which we base our everyday lives. However, not only do these data depend on the scale of measurement, but also handling these data (e.g., to...

The proliferation of financial derivatives over the past decades, options in particular, has underscored the increasing importance of derivative pricing literacy among students, researchers, and practitioners. Derivative Pricing: A Problem-Based Primer...

Probability and Conditional Expectations bridges the gap between books on probability theory and statistics by providing the probabilistic concepts estimated and tested in analysis of variance, regression analysis, factor analysis, structural equation...

Uniquely reflects an engineering view to social systems in a wide variety of contexts of application Social Systems Engineering: The Design of Complexity brings together a wide variety of application approaches to social systems from an engineering...