If you are a researcher or student with experience in multiple linear regression and want to learn about logistic regression, Paul Allison's Logistic Regression Using SAS: Theory and Application, Seco
Using numerous examples and practical tips, this book offers a nontechnical explanation of the standard methods for missing data (such as listwise or casewise deletion) as well as two newer (and, bett
Drawing on recent "event history" analytical methods from biostatistics, engineering, and sociology, this book explains how longitudinal data can be used to study the causes of deaths, crimes, wars, a
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
This extremely well-written, straightforward book gives you the flexibility to cover regression more thoroughly than do most statistics texts, without financially taxing your students.AyIt is written
Thomas Carlyle and the Idea of Influence positions Carlyle as an ideal representative figure through which to study that complex interplay between past and present most commonly referred to as influen
