SCS Reads 2008
Go to: SCS:_Seminars_2008-09 for information on the seminars this year
The following books were in contention:
Inspired by CBC's 'Canada Reads' annual competition, this is a list of nominees for SCS Seminars in 2008-2009.
- Donald B. Rubin (2006) Matched Sampling for Causal Effects. Cambridge.
- This is a collection of quite readable papers by Rubin and co-authors from the 70s to the early 2000s. They develop the theme of causal inference from observational data in a broader and more accessible way than focussing wholly on recent work in propensity scores. The material is conceptually dense but mathematically tractable. Some members could easily elucidate the math when it gets a bit thick.
- Frank E. Harrell (2001) Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis. Springer.
- Harrell's book is very pertinent to our recent discussions on model building and selection. In contrast with Rubin's book, its focus is predictive modeling, not causal modeling.
- Sawilowsky, S.S. (2007). Real Data Analysis. Charlotte, NC: Information Age Publishing.
- Publisher's description: http://www.infoagepub.com/products/content/978-1-59311-565-4.php
- Limited Preview on Google Books: http://books.google.ca/books?id=C_bV8CKr7asC&client=firefox-a
- Morgan, Stephen L. and Winship, Christopher (2007) Counterfactuals And Causal Inference Cambridge University Press
- John Fox's review for Canadian Journal of Sociology: http://wiki.math.yorku.ca/images/9/97/Morgan-Winship-review.pdf
- Yu, Chong Ho [Alex] (2006) Philosophical foundations of quantitative research methodology University Press of America, c2006.  (http://www.creative-wisdom.com/)
- Hill, Jennifer and Gelman, Andrew (2007) Data Analysis Using Regression and Multilevel/Hierarchical Models (http://www.stat.columbia.edu/~gelman/arm/) Cambridge.
- This book seems to have the answer to all my questions that I didn't know how to ask. For example, it has two excellent chapters on causal inference that are remarkably clear, a discussion on mediation and principal stratification, extensive materials on Bayesian inference. It is intended for graduate students in political science, etc., and covers with simple mathematics but with considerable clarity many 'modern' statistical issues. All methods are illustrated with clear code in R and BUGS.
- Adèr, Herman.J., Mellenbergh, Gideon J., & Hand David J. (2008). Advising on research methods: A consultant's companion. Huizen, The Netherlands: Johannes van Kessel Publishing. ISBN 978-90-79418-01-5.
- From Manolo:
- Although I don't think I'll be reviewing it any time soon, its description and table of contents look pretty interesting and a propos for the SCS seminar:
- Publisher's description: http://www.jvank.nl/ARMHome/
- Google Books: http://books.google.com/books?id=LCnOj4ZFyjkC&dq=Advising+on+research+methods&source=gbs_summary_s&cad=0
- Jason Osborne (Ed.) [Best Practices in Quantitative Methods. http://jwosborne.com/bestpractices_index.html