**Political Science 7963**
**Research Methods and Statistics II:**
**Regression Analysis**
**Instructor: Professor K. Bratton**
**Time: Friday, 9-12**
**Office Hours: Friday, Wednesday, Thursday 11-12**
**Office Phone: 578-1912**
**Home Phone: 343-9820**
**Email: ****bratton@lsu.edu**
**Course Objectives**
In this course, we will study multiple regression in depth, focusing on the theoretical foundations and the practical applications of regression analysis. We will begin with an in-depth review of bivariate regression, and move from there to multiple regression. We will examine a number of problems encountered in regression analysis, including multicollinearity, non-linear relationships, non-interval independent variables, heteroscedasticity, and autocorrelation. Toward the end of class, we may introduce advanced topics.
**Student Responsibilities**
Course grades depend on the following:
1. Four problem sets (to be assigned) (the first worth 10% of the final grade, the following three each worth 15% of the final grade).
Problem sets involve not only generating computer output, but also (and more importantly) interpreting and evaluating results. Students have the option of using any of the computer statistical packages to which they have access. Students are required to turn in both their program syntax and their results.
The first problem set will be distributed in approximately 2 weeks.
2. A midterm (worth 20% of the final grade) and a final (worth 25% of the final grade). These will be closed book, but students will be allowed to bring in one sheet of notes.
**Assigned Texts**
Gujarati, Damodar. 1995. __Basic Econometrics__ (3rd ed. Or 4^{th} ed.) New York: McGraw Hill.
Berry, William D. and Stanley Feldman. 1985. __Multiple Regression in Practice__. Sage Publications #50.
Lewis-Beck, Michael S. 1980. __Applied Regression: An Introduction__. Sage Publications #22.
Jaccard, James, Robert Turrisi, and Choi K. Wan. __Interaction Effects in Multiple Regression__. Sage Publications #72.
**Course Schedule**
*(assigned reading is to be done in preparation for that class)*
**Friday, January 21**^{st}
Introduction
**Friday, January 28**^{th}
Review of 7962. Begin review of bivariate regression
**Friday, February 4**^{th}
Continue review of bivariate regression: Fitting a line, OLS assumptions, estimating a and ß. The estimated slope coefficient "b": variance of b, confidence interval for b, and hypothesis testing of b.
Assigned Reading:
Gujarati, Chapters 1-4, Sections 5.1-5.8, 5.9, 6.1-6.2
Lewis-Beck: p. 9-20, 26-38, 20-25.
**Friday, February 11**^{th}
Problem Set #1 Assigned.
Residuals as well as explained, unexplained, and total deviations and sums of squares. Standardized variables and standardized variable coefficients; regression forced through the origin. Functional transformations of independent variables. Interpolation, predictive intervals, extrapolation, and outliers. Aggregation bias. Diagnostic plots.
Assigned Reading:
Gujarati: Sections 6.3-6.9, 5.10-5.13
Lewis-Beck: p. 38-47
Recommended:
King, Gary. 1986. "How Not To Lie with Statistics: Avoiding Common Mistakes in Quantitative Political Science." __American Journal of Political Science__ 30: 666-687.
Lewis-Beck, Michael and Andrew Skalaban. 1991. "The R-Squared: Some Straight Talk." In __Political Analysis, Vol. 2__. Ann Arbor: The University of Michigan Press. Pp. 153-171.
##
## **Friday, February 18**^{th}
Introduction to Multiple Regression.
Assigned Reading
Gujarati chapters 7.1-7.4, 8.1-8.4
Lewis-Beck, pp. 47-52, 53-54
Recommended:
Achen, Christopher. 1991. "What Does 'Explained Variance' Explain?: Reply." In __Political Analysis, Vol. 2__. Ann Arbor: The University of Michigan Press. Pages 173-184.
King, Gary. 1991. "Stochastic Variation: A Comment on Lewis-Beck and Skalaban's 'The R-Squared'." In __Political Analysis, Vol. 2__. Ann Arbor: The University of Michigan Press. Pages 185-200.
**Friday, February 25**^{th}
Problem set #1 due; problem set #2 assigned.
Summary and review of partial effects, t-stats, prob-values, hypothesis testing. Interactions.
Required Reading:
Gujarati, Sections 7.5, 7.6, 7.8
Lewis-Beck, p. 52-53, 54-56
Berry and Feldman, p. 1-18
Jaccard, Turrisi, and Wan. All.
Recommended:
Friedrich, Robert J. 1982. "In Defense of Multiplicative Terms in Multiple Regression Equations." __American Journal of Political Science__ 26: 797-833.
Gill, Jeff. 1999. “Field Essay: The Insignificance of Null Hypothesis Significance Testing.” *Political Research Quarterly* 52(3).
**Friday, March 4**^{th}
Draft of Problem Set #2 due. Review.
**Friday, March 11**^{th}
## **Midterm I**
**Friday, March 18**^{th}
Problem Set #2 Due.
Multicollinearity and Multicollinearity diagnostics; dummy and categorical independent variables.
Assigned Reading
Gujarati, Chapter 10, Sections 15.1-15.5, 15.9
Lewis-Beck, p. 58-63, 66-71
Berry and Feldman, sections 4 and 5
**Friday, April 1**^{st}
Functional Transformations, model specification, missing data, measurement errors.
Assigned Reading:
Gujarati, Sec. 7.7, 7.9-7.12, Chapter 13
Berry and Feldman, sections 2 and 3
Lewis-Beck, p. 56-58, 63-66
**Friday, April 8**^{th}
Regression diagnostics and graphical techniques; analysis of variance and the f-test. Problem set #3 assigned. A closer look at categorical independent variables and f-tests.
Assigned Reading:
Gujarati, Sec. 8.5, 8.6-8.8, 15.6-15.8, 15.11, 15.15
Lewis-Beck, p. 71-74
Recommended:
Bollen, Kenneth and Robert Jackman. 1990. "Regression Diagnostics: An Expository Treatment of Outliers and Influential Cases." In John Fox and J. Scott Long, eds., __Modern Methods of Data Analysis__, Sage Publications, pp. 257-291.
Chatterjee, Samprit and F. Wiseman. "Use of Regression Diagnostics in Political Science Research." __American Journal of Political Science__ 27: 601-613.
Mock, Carol and Herbert F. Weisberg. "Political Innumeracy: Encounters with Coincidence, Improbability, and Chance." __American Journal of Political Science __36: 1023-1046.
**Friday, April 15**^{th}
Heteroscedasticity
Problem set #4 assigned; problem set #3 due.
Assigned Reading:
Gujarati, Chapter 11
Recommended:
Downs, George W. and David M. Rocke. (1979) "Interpreting Heteroscedasticity," __American Journal of Political Science__, v. 23, no. 4 (November) pp. 816-828.
Lemieux, Peter (1976) "Heteroscedasticity and Causal Inference in Political Research" __Political Methodology__ 3: 287-316.
**Friday, April 22**^{nd}
Autocorrelation
Assigned Reading:
Gujarati: Chapter 12
Berry and Feldman: Section 6
Recommended:
Hibbs, Douglas A. (1974) "Problems of Statistical Estimation and Causal Inference in Time-Series Regression Models," __Sociological Methodology__, pp. 252-308.
**Friday, April 29**^{th}
**Friday, May 6**^{th}
(Problem set #4 due during finals week)
**Share with your friends:** |