Multivariate Reduced-Rank Regression

"Preface Regression models are today a standard tool in medical research. However, their application and the interpretation of their results is often challenging. It is the purpose of this book to in

It is no exaggeration to say that virtually all quantitative research in the social sciences is done with correlation and regression analysis (CRA) and their siblings and offspring. CRA are fundamenta

Praise for the Fourth Edition:"This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable."—Journal of the American Statis

Praise for the Second Edition "This book is a systematic, well-written, well-organized text on multivariate analysis packed with intuition and insight . . . There is much practical wisdom in this book

Michael Mitchell's Interpreting and Visualizing Regression Models Using Stata is a clear treatment of how to carefully present results from model-fitting in a wide variety of settings. It is a boon to

This monograph is multivariate, multi-perspective and multipurpose. We intend to be innovatively integrative through statistical synthesis. Innovation requires capacity to operate in ways that are n

"Noted for its comprehensive coverage, this greatly expanded new edition now covers the use of univariate and multivariate effect sizes. A variety of measures and estimators are reviewed along with th

Noted for its comprehensive coverage, this greatly expanded new edition now covers the use of univariate and multivariate effect sizes. Many measures and estimators are reviewed along with their appli

This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for

The book focuses on the physical and mathematical foundations of model-based turbulence control: reduced-order modelling and control design in simulations and experiments. Leading experts provide elem

Several recent advances in smoothing and semiparametric regression are presented in this book from a unifying, Bayesian perspective. Simulation-based full Bayesian Markov chain Monte Carlo (MCMC) infe

The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. T

This second edition of Hilbe's Negative Binomial Regression is a substantial enhancement to the popular first edition. The only text devoted entirely to the negative binomial model and its many variations, nearly every model discussed in the literature is addressed. The theoretical and distributional background of each model is discussed, together with examples of their construction, application, interpretation and evaluation. Complete Stata and R codes are provided throughout the text, with additional code (plus SAS), derivations and data provided on the book's website. Written for the practising researcher, the text begins with an examination of risk and rate ratios, and of the estimating algorithms used to model count data. The book then gives an in-depth analysis of Poisson regression and an evaluation of the meaning and nature of overdispersion, followed by a comprehensive analysis of the negative binomial distribution and of its parameterizations into various models for evaluatin

Pons (Institute of Agronomic Research, France) presents new mathematical results about statistical methods for the density and regression functions, which appear widely in the mathematical literature.

Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data sets, enabling readers to answer increasingly complex resear

Simultaneous confidence bands enable more intuitive and detailed inference of regression analysis than the standard inferential methods of parameter estimation and hypothesis testing. Simultaneous Inf

Find the right algorithm for your image processing applicationExploring the recent achievements that have occurred since the mid-1990s, Circular and Linear Regression: Fitting Circles and Lines by Lea

An examination of mathematical formulations of ridge-regression-type estimators points to a curious observation: estimators can be derived by both Bayesian and Frequentist methods. In this updated an

"Random matrix theory has a long history, beginning in the first instance in multivariate statistics. It was used by Wigner to supply explanations for the important regularity features of the apparent

This book provides actuarial and finance students with a foundation in multiple regression and time series, along with a discussion of advanced statistical topics that are relevant to actuarial and fi

This book focuses on tools and techniques for building valid regression models using real-world data. A key theme throughout the book is that it only makes sense to base inferences or conclusions on v

This book focuses on tools and techniques for building regression models using real-world data and assessing their validity. A key theme throughout the book is that it makes sense to base inferences o

Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences shows students how to apply statistical methods to behavioral science data in a sensible manner. Assuming some familiarity

An applied treatment of the key methods and state-of-the-art tools for visualizing and understanding statistical data Smoothing of Multivariate Data provides an illustrative and hands-on approach to

Yan (U. of Missouri-Kansas City) and Su (U. of Central Florida) present this work as a one-semester textbook for a course in regression analysis for graduate students majoring in statistics and biosta

This set contains ISBN 978-0-470-08186-0 Modern Regression Methods, 2nd Edition and the Solutions Manual 978-0-470-09606-2.

This book demonstrates how to estimate and interpret fixed-effects models in a variety of different modeling contexts: linear models, logistic models, Poisson models, Cox regression models, and struc

"Over the years, I have had the opportunity to teach several regression courses, and I cannot think of a better undergraduate text than this one." (The American Statistician) "The book is well writte

Statistical Learning from a Regression Perspective considers statistical learning applications when interest centers on the conditional distribution of the response variable, given a set of predictors

This set contains: 9780471469438 Regression and ANOVA: An Integrated Approach Using SAS(R) Software by Keith E. Muller, Bethel A. Fetterman and 9780471370383 Applied Statistics: Analysis of Variance a

This set contains: 9780471483076 SAS Regression Using JMP(r) by Rudolf Freund, Ramon Littell, Lee Creighton and 9780471210771 Experimental Design by Thomas P. Ryan.

Sensory scientists are often faced with making business decisions based on the results of complex sensory tests involving a multitude of variables. Multivariate and Probabilistic Analyses of Sensory S

“A welcome addition to multivariate analysis. The discussion is lucid and very leisurely, excellently illustrated with applications drawn from a wide variety of fields. A good part of the book can be

Regression analysis has become a mainstay of research in diverse fields; in this edition the authors take this popularity into consideration along with the fact that computers are everywhere. They cov

Reviewing the theory of the general linear model (GLM) using a general framework, Univariate and Multivariate General Linear Models: Theory and Applications with SAS, Second Edition presents analyses

Incorporates mixed-effects modeling techniques for more powerful and efficient methods This book presents current and effective nonparametric regression techniques for longitudinal data analysis and

This book studies and applies modern flexible regression models for survival data with a special focus on extensions of the Cox model and alternative models with the aim of describing time-varying eff

This volume celebrates the innovative and rapidly growing area of economic research known as meta-regression analysis (MRA).Shows how MRA enables researchers to make sense of disparate economic findin

Logistic Regression Models for Ordinal Response Variables provides applied researchers in the social, educational, and behavioral sciences with an accessible and comprehensive coverage of analyses fo

Orbiting spacecraft provide a valuable laboratory for experiments on physical and biological systems in a reduced gravity environment. Materials processing experiments have commonly involved the growth of crystals from the melt or solution, and the processing of alloys and composites. Biological experiments have been performed on a variety of subjects, including protein crystal growth, bio-reactors, and the adaptation of humans to extended periods of weightlessness. In these studies, fluid masses containing bubbles and drops are encountered routinely. This 2001 book provides a clear, thorough review of the motion of bubbles and drops in reduced gravity, particularly motion caused by variations in interfacial tension arising from temperature gradients on their surfaces. The emphasis is on theoretical analysis from first principles; experimental results are discussed and compared with predictions where appropriate. Students and researchers interested in fluid mechanics in reduced gravit