Regression Analysis: A Constructive Critique
identifies a wide variety of problems with regression analysis as it is commonly used and then provides a number of ways in which practice could be improved. Regression is most useful for data reduction, leading to relatively simple but rich and precise descriptions of patterns in a data set. The emphasis on description provides readers with an insightful rethinking from the ground up of what regression analysis can do, so that readers can better match regression analysis with useful empirical questions and improved policy-related research.
"An interesting and lively text, rich in practical wisdom, written for people who do empirical work in the social sciences and their graduate students."
--David A. Freedman, Professor of Statistics, University of California, Berkeley
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"Berk has incisively identified the various strains of regression abuse and suggests practical steps for researchers who desire to do good social science while avoiding such errors."
(Peter H. Rossi)"I have been waiting for a book like this for some time. Practitioners, especially those doing applied work, will have much to gain from Berk's volume, regardless of their level of statistical sophistication. Graduate students in sociology, education, public policy, and any number of similar fields should also use it. It will also be a useful foil for conventional texts for the teaching of the regression model. I plan to use it for my students as a text, and hope others will do the same."
(Herbert Smith)"An interesting and lively text, rich in practical wisdom, written for people who do empirical work in the social sciences and their graduate students."
(David A. Freedman)Preface
1. Prologue: Regression Analysis as Problematic
2. A Grounded Introduction to Regression Analysis
3. Simple Linear Regression
4. Statistical Inference for Simple Linear Regression
5. Causal Inference for the Simple Linear Model
6. The Formalities of Multiple Regression
7. Using and Interpreting Multiple Regression
8. Some Popular Extensions of Multiple Regression
9. Some Regression Diagnostics
10. Further Extensions of Regression Analysis
11. What to Do
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