This book integrates recent methodological developments for calculating the sample size and power in trials with more than one endpoint considered as multiple primary or co-primary, offering an important reference work for statisticians working in this area.

The determination of sample size and the evaluation of power are fundamental and critical elements in the design of clinical trials. If the sample size is too small, important effects may go unnoticed; if the sample size is too large, it represents a waste of resources and unethically puts more participants at risk than...

This book examines in detail the correlation, more precisely the weighted correlation and applicationsinvolving rankings. A general applicationis the evaluation of methods to predict rankings. Others involverankings representing human preferences to infer user preferences; the use of weighted correlation with microarray data and those in the domain of time series. In this book we presentnewweightedcorrelation coefficients and new methods of weighted principal component analysis.

We also introduce new methods of dimension reduction and clustering for time series data and describe some...

This is the first book to provide a comprehensive introduction to a new modeling framework known as semiparametric structural equation modeling and its technique, with the fundamental background needed to understand it. It offers a general overview of the basics of semiparametric structural equation models for causal discovery, estimation principles and algorithms, and applications in neuroscience, economics, epidemiology, and more.

Semiparametric structural equation modeling is one of the most exciting new topics in the field of causal discovery. This new framework assumes...

This book provides a concise summary of statistical inferences with random combinatorial models, especially random partitions and related models, with necessary theoretical backgrounds. Random combinatorial models have been developed at the interface of probability and combinatorics. They are useful for data analyses; however, statistical issues have been raised in each field and a general overview has not been given. This book presents a unified treatment of methods of statistical inferences with random combinatorial models. It begins with an introduction of various kinds of...

This book considers specific inferential issues arising from the analysis of dynamic shapes with the attempt to solve the problems at hand using probability models and nonparametric tests. The models are simple to understand and interpret and provide a useful tool to describe the global dynamics of the landmark configurations. However, because of the non-Euclidean nature of shape spaces, distributions in shape spaces are not straightforward to obtain.

The book explores the use of the Gaussian distribution in the configuration space, with similarity transformations integrated out....

Since Sir David Cox s pioneering work in 1972, the proportional hazards model has become the most important model in survival analysis. The success of the Cox model stimulated further studies in semiparametric and nonparametric theories, counting process models, study designs in epidemiology, and the development of many other regression models that could offer more flexible or more suitable approaches in data...