SCS: Seminars 2008-09
From MathWiki
- For the list of books that were in contention see SCS Reads 2008
- For links related to the book we selected, see Gelman & Hill (2007)
- R: Gelman & Hill makes intensive use of R (http://cran.r-project.org/). There is a wiki page on getting started with R.
| Table of contents |
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Week 1: Gelman & Hill Chapters 1 and 2
- Friday, September 19, 2008 at 2:30 pm
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Data sets
- coop (http://www.stat.columbia.edu/~gelman/arm/examples/coop): tallies from an election for the board of a cooperative housing organization, used in Chapter 2 for testing the hypothesis of underdispersion in count data
- death.polls (http://www.stat.columbia.edu/~gelman/arm/examples/death.polls): time series of Gallup polls on the death penalty, used in Chapter 2 to show simple confidence intervals
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Week 2: Gelman & Hill Chapters 3, 4, 5
- Friday, October 3, 2008 at 2:30 pm
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Data sets
- beauty (http://www.stat.columbia.edu/~gelman/arm/examples/beauty): Daniel Hamermesh's data on beauty and teaching evaluations, used in regression exercises in Chapters 3 and 4
- child.iq (http://www.stat.columbia.edu/~gelman/arm/examples/child.iq): study of children's IQ's used in Chapter 3 to illustrate linear regression
- earnings (http://www.stat.columbia.edu/~gelman/arm/examples/earnings): data on height, weight, earnings, and other variables from a national survey (Chapters 4 and 13)
- girls (http://www.stat.columbia.edu/~gelman/arm/examples/girls): the proportion of girl births in Vienna for 24 consecutive months, from Mises (1953), used in an exercise in Chapter 2 for testing the binomial model
- pyth (http://www.stat.columbia.edu/~gelman/arm/examples/pyth): simple dataset for a linear regression exercise in Chapter 3
- arsenic (http://www.stat.columbia.edu/~gelman/arm/examples/arsenic): data on switching drinking water wells in Bangladesh, used in Chapter 5 to illustrate logistic regression
- nes (http://www.stat.columbia.edu/~gelman/arm/examples/nes): data from the National Election Study, used in Chapters 4 and 5 to show a time series of linear and logistic regressions and in an exercise in Chapter 5 to illustrate nonidentifiability in logistic regression
- pollution (http://www.stat.columbia.edu/~gelman/arm/examples/pollution): old dataset of mortality and pollution in 60 U.S. cities, used in an exercise in Chapter 4 to illustrate transformations in linear regression
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Week 3: Gelman & Hill Chapters 5,6
- Friday, October 17, 2008 at 2:30 pm
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Week 4: Gelman & Hill Chapters 7,8
- Friday, October 31, 2008 at 2:30 pm
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Week 5: Gelman & Hill Chapters 8, 9
- Friday, February 13, 2009 at 2:30 pm
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Week 6:Gelman & Hill Chapters 9 and 10
- Friday, February 27, 2009 at 2:30 pm
Hugh McCague to give a presentation on circular statistics
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Week 7:Gelman & Hill Chapters 10 and 11
- Friday, March 13
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Week 8 Lord's Paradox: Gain scores or ANCOVA
- Friday, April 3 (MOVED -- no longer March 27)
Readings on Lord's paradox previously circulated via email:
- Lord, F. (1967). A Paradox in the Interpretation of Group Comparisons. Psychological Bulletin, 68, 304-305. (http://csaweb109v.csa.com.ezproxy.library.yorku.ca/ids70/view_record.php?id=1&recnum=5&log=from_toc&SID=4qd8tsaa4ughl8tjd06m7fbq17&mark_id=cache:0,0,13)
- Lord, F. (1969). Statistical Adjustments When Comparing Preexisting Groups. Psychological Bulletin, 72, 336-337. (http://csaweb109v.csa.com.ezproxy.library.yorku.ca/ids70/view_record.php?id=5&recnum=8&log=from_toc&SID=4qd8tsaa4ughl8tjd06m7fbq17&mark_id=cache:2,0,12)
- Daniel B. Wright, D. B. (2006). Comparing groups in a before–after design: When t test and ANCOVA produce different results, British Journal of Educational Psychology, 76, 663-675. (http://www.ingentaconnect.com.ezproxy.library.yorku.ca/content/bpsoc/bjep/2006/00000076/00000003/art00014)
- Friedman, L. and W. Wall. (2005). Graphical Views of Suppression and Multicollinearity in Multiple Linear Regression. The American Statistician, 59, 127-136. (http://proquest.umi.com.ezproxy.library.yorku.ca/pqdweb?index=7&did=831692351&SrchMode=3&sid=1&Fmt=6&VInst=PROD&VType=PQD&RQT=309&VName=PQD&TS=1237789833&clientId=5220&aid=1)
- "Emerging+Themes+in+Epidemiology":And:LQE%3D(DA,None,8)20080122:And:LQE%3D(VO,None,1)5$&sgHitCountType=None&inPS=true&sort=DateDescend&searchType=PublicationSearchForm&tabID=T002&prodId=AONE&searchId=R1¤tPosition=1&userGroupName=yorku_main&docId=A175408362&docType=IAC Yu-Kang Tu, Y.-K., D. Gunnell and M. S. Gilthorpe. (2008). Simpson's Paradox, Lord's Paradox, and Suppression Effects are the same phenomenon – the reversal paradox. Emerging Themes in Epidemiology, 5(2) (http://find.galegroup.com.ezproxy.library.yorku.ca/itx/retrieve.do?contentSet=IAC-Documents&resultListType=RESULT_LIST&qrySerId=Locale(en,US,):FQE%3D(JN,None,33))
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Some references
- Rogosa, D. R., & Willett, J. B. (1983). Demonstrating the reliability of the difference score in the measurement of change. Journal of Educational Measurement, 20, 335-343.
- Rogosa, D. (1988). Myths about longitudinal research. In K. W. Schaie, R. T. Campbell, W. M. Meredith, & S. C. Rawlings (Eds.), Methodological issues in aging research (pp. 171-209). New York, NY: Springer Publishing Company.
- Maris, E. (1998). Covariance adjustment versus gain scores--revisited. Psychological Methods, 3, 309-327.
- Maxwell, S. E., & Delaney, H. D. (1990). Designing experiments and analyzing data: A model comparison approach. Belmont, CA: Wadsworth.
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Links
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Multilevel models
- A First Look at Multilevel and Longitudinal Models (http://www.math.yorku.ca/~georges/Courses/Repeated/CourseNotes.pdf) (userid:fisher password:cohen)
- Longitudinal Data Analysis with Mixed Models: A Graphical Overview (http://www.math.yorku.ca/~georges/Slides/Workshop-v1-0Slides.pdf)
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Week 9: Gelman & Hill Chapters 11,12
- Friday, April 24, 2008 at 2:30 pm
