Bias and Causation: Models and Judgment for Valid Comparisons

"The book combines a useful synthesis of the literature with an original working through of issues related to bias and causal inference. Anyone with a sustained interest in this topic will find the book worth reading." (Journal of Educational and Behavioral Statistics, May 2012)

"...the book provides a unified framework for understanding issues of causal inference discussed differently across disciplines...the book will also be of substantial interest to methodologically minded readers working within specific disciplines but interested in methodological literature from other disciplines." (Journal of Educational and Behavioral Statistics, May 2012)

"The book covers almost all the relevant biases that can be present when designing and analyzing treatment effects in comparative studies." (Journal of Biopharmaceutical Statistics, January 2011)"A consultant who specializes in applying statistics to various business and legal issues, Weisberg explains approaches to bias and causal inference, a realm statisticians have avoided until recently because it requires intuitive skills beyond the pale of mathematics. He writes for practicing researchers and methodologists and for students with a reasonably solid grounding in basic statistics and research methods." (SciTech Book News, December 2010)