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Applied Logistic Regression Analysis Paperback – Oct 9 2001
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About the Author
Scott Menard is a Professor of Criminal Justice at Sam Houston State University and a research associate in the Institute of Behavioral Science at the University of Colorado, Boulder. He received his A.B. at Cornell University and his Ph.D. at the University of Colorado, Boulder, both in Sociology. His interests include quantitative methods and statistics, life course criminology, substance abuse, and criminal victimization. His publications include Longitudinal Research (second edition Sage 2002), Applied Logistic Regression Analysis (second edition Sage 2002), Good Kids from Bad Neighborhoods (Cambridge University Press 2006, with Delbert S. Elliott, Bruce Rankin, Amanda Elliott, William Julius Wilson, and David Huizinga), Youth Gangs (Charles C. Thomas 2006, with Robert J. Franzese and Herbert C. Covey), and the Handbook of Longitudinal Research (Elsevier 2008), as well as other books and journal articles in the areas of criminology, delinquency, population studies, and statistics.
Inside This Book(Learn More)
In linear regression analysis, it is possible to test whether two variables are linearly related and to calculate the strength of the linear relationship if the relationship between the variables can be described by an equation of the form Y = a + BX, where Y is the variable being predicted (the dependent, criterion, outcome, or endogenous variable), X is a variable whose values are being used to predict Y (the independent, exogenous, or predictor variable),1 and a and B are population parameters to be estimated. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Back Cover
Most Helpful Customer Reviews on Amazon.com (beta)
When compared to SAS's documentation, this book's greatest advantage is explaining in english (rather than mathematical notation) the assumptions and limitations of SAS's (and SPSS'S) algorithms. Its chapter on logistic regression diagnostics is alone worth the price of the book. In short, if you need to use logistic regression analysis and you already understand OLS, you cannot go wrong with this book.
Before I bought Menard's introduction, I tried to improve my understanding of logistic regression, including proper interpretation of unstandardized coefficients and various measures of goodness of fit, with the first edition of Hosmer and Lemeshow's Applied Logistic Regression. Compared to Mendard's book, however, Hosmer and Lemeshow's presentiation is tedious, plodding, and needlessly dense. Apparently it was written for an audience to which I do not belong.
I use logistic regression fairly often, and I have yet to encounter an issue that I couldn't address through reference to Menard's Applied Logistic Regression Analysis. The explanations are clear, the formulas are easy to follow, and the examples are instructive. An awful lot of useful information is packed into one brief and inexpensive document.
I bought and I'm glad I did, but I don't refer to it like I do Hosmer and Lemeshow's text.
I eagerly await the next edition of this monograph. Thank you!
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