Applied Regression Analysis and Multivariable Methods

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 cover concepts and examples of research, classification of variables and the choice of analysis, statistics, the workings of regression analysis, straight-line regression analysis, the correlation coefficient and straight-line regression analysis, the analysis of variable table, multiple regression analysis, testing hypotheses in multiple regression, various types of correlation, confounding and interactions, dummy variables, adjusting continuous data, regression diagnoses, polynomial regression, selecting the best regression equation, one-way analysis of variance, randomized blocks, two-way anova with equal and unequal cell numbers, maximum likelihood, logistic regression analysis, polytomous and ordinal logistic regression, Poisson regression analysis, analysis of co-related data, and sample size planning for linear and logistic regression and analysis of variance. Annotation c2007 Book News, Inc., Portland, OR (booknews.com)