Aug

26

Speaking of regression

August 26, 2024 |

A Primer on Correlation and Regression, by Victor Niederhoffer
(07-Nov-2006)

Applying Regression and Correlation: A Guide for Students and Researchers, by Jeremy Miles of the RAND Corporation and Mark Shevlin of the University of Ulster, illustrates the proper and pitfall-laden path that leads to the many beautiful and illuminating things that correlation and regression can accomplish. The book is written for psychology students without any training in calculus, and it contains simple examples and extensive commentary on the regression output from standard statistical programs such as SPSS. However, the applications for psychology are almost identical to those that would be used in markets, with such variables as industries substituted for classes and companies for individuals.

And what a wonderful array of applications and extensions this book contains. I found myself augmenting my knowledge or learning something new on almost every page, and I have read many dozens of books on this subject. There are great sections on how to code your data so that you can do categorical regression, categorical covariance, structural equation analysis. There is a very good section on how to go through all the steps of logistic regression with simple examples and calculations to show how the maximum likelihood solution is computed. There is a very fine discussion of the reasons that you should never use stepwise regression and why hierarchical regression is much better. There is a complete chapter on all the computational methods of measuring the individual contributions to the prediction and the influence of each independent variable and each observation in the regression.

One of the main themes of the book that hold everything together is that everything that can be done with the usual analysis of variance techniques can be done with regression, but that regression does so much more. While I had read this before, I had never seen such a clear exposition of how to code the data so that you can actually accomplish the transformation and always come up with the more complete and useful regression solutions to such problems.

Read the complete review.


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