Practical Statistical Methods: A SAS Programming Approach

Book Preface

This book discusses various statistical methods aimed at a diverse audience. A broad spectrum of methods is given that will be useful for researchers without much statistical background. Omitting mathematical details and complicated formulae, SAS programs are provided to carry out the necessary analyses and draw appropriate inferences for statistical problems that are widely used by most researchers. Similar types of programs can be used with other statistical packages, drawing similar conclusions. The book emphasizes the different, commonly used methodologies and interpretation of the data using SAS version 9.1.

Practical Statistical Methods: A SAS Programming Approach will assist researchers in all fields, including those in the pharmaceutical industry, the biological sciences, physical sciences, social sciences, market research, and psychology. Additionally, it will be a reference book for applied statisticians working with researchers in the fields indicated above. It will also be helpful as supplemental reading material for graduate students taking a statistical methods course for one or two semesters.

Fundamental statistical concepts are introduced in Chapter 1 and the methods used for quantitative data, continuous data following normal and nonnormal distributions, are discussed in Chapters 2 through 4. Regression methodology starting with simple linear regression and discussing logistic regression and PH regression are highlighted in Chapter 5. Chapter 6 briefly sketches miscellaneous topics such as propensity scores, cutoff points of a marker indicating the end point, misclassification errors, interim analysis, conditional power, bootstrap and jackknife, among others.