Now in its third edition, this highly successful text has been fully revised and updated with expanded sections on cutting-edge techniques including Poisson regression, negative binomial regression, multinomial logistic regression and proportional odds regression. As before, it focuses on easy-to-follow explanations of complicated multivariable techniques. It is the perfect introduction for all clinical researchers. It describes how to perform and interpret multivariable analysis, using plain language rather than complex derivations and mathematical formulae. It focuses on the nuts and bolts of performing research, and prepares the reader to set up, perform and interpret multivariable models. Numerous tables, graphs and tips help to demystify the process of performing multivariable analysis. The text is illustrated with many up-to-date examples from the medical literature on how to use multivariable analysis in clinical practice and in research.
Structural Sensitivity in Econometric Models Edwin Kuh, John W. Neese and Peter Hollinger Provides a pathbreaking assessment of the worth of linear dynamic systems methods for probing the behavior of...
This book traces the theory and methodology of multivariate statistical analysis and shows how it can be conducted in practice using the LISREL computer program. It presents not only the typical uses...
This book provides an introduction to the analysis of multivariate data.It describes multivariate probability distributions, the preliminary analysisof a large -scale set of data, princ iple...
Data analysis is a vital part of science today, and in assessing quality, multivariate analysis is often necessary in order to avoid loss of essential information. Martens provides a powerful and...