Political Science 787: Multivariate Analysis
Fall 2013
Monday 4-6 (5564 Haven)
Professor: Walter R. Mebane, Jr.
Office: 7735 Haven Hall (607/592-0546); email
wmebane@umich.edu
Office hours: Wed 2-4 or other times by appointment.
Course web page: in CTools; syllabus also at
http://www.umich.edu/ wmebane/ps787.html
Assignment Due Dates |
due date |
description |
weight |
TBA |
four data analysis problem sets |
70% |
Dec 20 |
final paper |
20% |
-- |
participation |
10% |
See fpaper.pdf posted on the CTools site for more information about
the final paper. The presentation described there will be rated as part of
the participation grade.
Reading Availability
Much of the course will refer to journal articles. I plan to follow or refer
to a few chapters in the following books (others also appear below).
- Cameron, A. Colin, and Pravin K. Trivedi. 2005.
Microeconometrics: Methods and Applications.
Cambridge UP.
- Kenneth E. Train. 2003.
Discrete Choice Methods with Simulation.
Cambridge UP.
In the following listing, required reading is preceded by a bullet. Other
items are recommended.
Class meeting and reading schedule
- computing (Sep 9)
- Crawley, Michael R. 2007. The R Book. Wiley.
- Spector, Phil. 2008. Data manipulation with R. Springer.
- Albert, Jim. 2007. Bayesian Computation with R. Springer.
- Chambers, John M. 2008. Software for Data Analysis. Springer.
- Braun, W. John, and Duncan J. Murdoch. 2007.
A First Course in Statistical Programming with R. Cambridge.
- Plummer, Martyn. 2003.
``JAGS: A Program for Analysis of Bayesian Graphical Models Using Gibbs Sampling,''
Proceedings of the 3rd International Workshop on Distributed Statistical
Computing (DSC 2003), March 20-22, Vienna, Austria. ISSN 1609-395X.
http://www.ci.tuwien.ac.at/Conferences/DSC-2003/Proceedings/Plummer.pdf
- JAGS.
http://mcmc-jags.sourceforge.net/
- asymptotics, bootstrap and refinements (Sep 16)
- Bradley Efron. 1987.
``Better Bootstrap Confidence Intervals (and discussion)''
Journal of the American Statistical Association 82 (397): 171-200.
- Gary W. Oehlert. 1992.
A Note on the Delta Method.
The American Statistician 46 (1, Feb.): 27-29.
- Thomas R. Fears, Jacques Benichou, Mitchell H. Gail. 1996.
A Reminder of the Fallibility of the Wald Statistic.
The American Statistician 50 (3, Aug.): 226-227.
- Yudi Pawitan. 2000.
A Reminder of the Fallibility of the Wald Statistic: Likelihood Explanation.
The American Statistician 54 (1, Feb.): 54-56.
- J. Scott Long and Laurie H. Ervin. 2000.
Using Heteroscedasticity Consistent Standard Errors in the Linear Regression Model.
The American Statistician 54 (3, Aug.): 217-224.
- Dennis D. Boos and Jacqueline M. Hughes-Oliver. 2000.
How Large Does Have to be for and Intervals?
The American Statistician 54 (2, May): 121-128.
- Bradley Efron. 1979.
``Bootstrap Methods: Another Look at the Jackknife,''
Annals of Statistics 7 (1): 1-26.
- Barndorff-Nielsen, O. E., and D. R. Cox. 1984.
``Bartlett Adjustments to the Likelihood Ratio Statistic and the Distribution
of the Maximum Likelihood Estimator,''
Journal of the Royal Statistical Society. Series B (Methodological)
46 (3): 483-495.
- A.C. Davison and D.V. Hinkley. 1997.
Bootstrap Methods and their Applications. Cambridge.
- Cameron and Trivedi. Chapters 5, 11 and Appendix A.
- Jeffrey M. Wooldridge. 2002.
Econometric Analysis of Cross Section and Panel Data. MIT Press.
Chapters 3, 12-14.
- Russell Davidson and James G. MacKinnon. 1993.
Estimation and Inference in Econometrics. Oxford UP.
Chapters 4, 8-9.
- choice models (Sep 23, 30, Oct 7)
- Daniel McFadden and Kenneth Train. 2000.
Mixed MNL Models for Discrete Response.
Journal of Applied Econometrics 15 (5, Sep-Oct): 447-470.
- Kenneth E. Train. 2009.
Discrete Choice Methods with Simulation. 2d ed.
Cambridge UP.
http://elsa.berkeley.edu/books/choice2.html
- John E. Jackson, Bogdan W. Mach and Radoslaw Markowski. 2010.
``Party Strategies and Electoral Competition in Post-Communist Countries:
Evidence from Poland.''
Electoral Studies 29 (2): 199-209.
(in file jackson.mach.markowski.elecstud2010.pdf)
- John E. Jackson, Bogdan W. Mach and Radoslaw Markowski. 2010.
``Party Strategies and Electoral Competition in Post-Communist Countries:
Evidence from Poland. Appendix A: Methodological Appendix.''
(in file jelsmethapp.docx)
- Walter R. Mebane, Jr. 2013.
``A mixed logit model with 1997 Polish survey data from John Jackson.''
Working paper (in file notes27sep2013.pdf).
- Garrett Glasgow. 2001.
Mixed Logit Models for Multiparty Elections.
Political Analysis 9 (1): 116-136.
- Hensher, David A., and William H. Greene. 2003.
The mixed logit model: the state of practice.
Transportation 30 (2): 133-176.
- McFadden, Daniel. 1974.
``Conditional logit analysis of qualitative choice behavior.''
In P Zarembka, ed.,
Frontiers of Econometrics, New York: Acadmic Press. pages
105-142.
http://emlab.berkeley.edu/reprints/mcfadden/zarembka.pdf
- McFadden, Danel. 1981.
``Structural Discrete Probability Models Derived from
Theories of Choice.'' In Charles F. Manski and Daniel L. McFadden, eds,
Structural
Analysis of Discrete Data and Econometric Applications, Cambidge, MA: MIT Press,
chapter 5, pp. 198-272.
http://emlab.berkeley.edu/discrete/ch5.pdf
- hierarchical models, MCMC (Oct 21, 28)
- Simon Jackman. 2009.
Bayesian Analysis for the Social Sciences. Wiley. Chapter 7.
- Andrew Gelman, John B. Carlin, Hal S. Stern and Donald B. Rubin. 2004.
Bayesian Data Analysis, 2d ed. Chapman & Hall. Chapter 5.
(Chapters 1-4 are probably necessary preparation.)
- Andrew Gelman and Jennifer Hill. 2007.
Data Analysis Using Regression and Multilevel/Hierarchical Models.
Cambridge. Pages 109-117 251-265, 345-359, 366-371, 419-421.
- Brooks, S. P. 1998. Markov chain Monte Carlo method and its application.
The Statistician 47: 69-100.
- Brooks, S. P. and A. Gelman. 1998. Alternative methods for monitoring
convergence of iterative simulations.
Journal of Computational and Graphical Statistics 7: 434-455.
- Spiegelhalter, D. J., N. G. Best, B. P. Carlin and A. van der Linde. 2002.
Bayesian measures of model complexity and fit (with discussion).
J. Roy. Statist. Soc. B 64: 583-640.
- George Casella and Edward I. George. 1992.
Explaining the Gibbs Sampler
The American Statistician 46 (3, Aug.): 167-174.
- Siddhartha Chib and Edward Greenberg. 1995.
Understanding the Metropolis-Hastings Algorithm
The American Statistician 49 (4, Nov.): 327-335.
- Jeff Gill. 2002.
Bayesian Methods: A Social and Behavioral Approach. Chapman &
Hall.
- latent variable models (Nov 4)
- Simon Jackman and Shawn Treier. 2008.
Democracy as a Latent Variable.
American Journal of Political Science 52 (1): 201-217.
- Joshua Clinton, Simon Jackman and Douglas Rivers. 2004.
The Statistical Analysis of Roll Call Data.
American Political Science Review 98 (2, May): 355-370.
- Jian-Qing Shi and Sik-Yum Lee. 2000.
Latent Variable Models with Mixed Continuous and Polytomous Data.
Journal of the Royal Statistical Society. Series B (Statistical
Methodology) 62 (1): 77-87.
- Vincent Arel-Bundock and Walter R. Mebane, Jr. 2011.
``Measurement Error, Missing Values and Latent Structure in Governance
Indicators''.
Paper presented at the 2011 Annual Meeting of the American Political Science
Association, Seattle, WA, September 1-4.
- Michael A. Bailey. 2007.
Comparable Preference Estimates across Time and Institutions for the
Court, Congress, and Presidency.
American Journal of Political Science 51 (3, Jul.): 433-448.
- Sik-Yum Lee. 2007.
Structural Equation Modelling: A Bayesian Approach. Wiley.
- Sik-Yum Lee, Xin-Yuan Song, John C. K. Lee. 2003.
Maximum Likelihood Estimation of Nonlinear Structural Equation Models with Ignorable
Missing Data.
Journal of Educational and Behavioral Statistics 28 (Summer): 111-134.
- Sik-Yum Lee and Xin-Yuan Song. 2004.
Maximum Likelihood Analysis of a General Latent Variable Model with
Hierarchically Mixed Data.
Biometrics 60 (Sep.): 624-636.
- Sophia Rabe-Hesketh, Anders Skrondal and Andrew Pickles. 2004.
Generalized Latent Variable Modelling: Multilevel, Longitudinal and
Structural Equation Models. Chapman & Hall.
- hypothesis tests, M-estimators and QMLE (Nov 11)
- Cameron and Trivedi. Chapter 7.
- Benjamini, Yoav and Yosef Hochberg. 1995.
Controlling the False Discovery Rate: A Practical and Powerful
Approach to Multiple Testing.
Journal of the Royal Statistical Society, Series B 57 (1): 289-300.
- Benjamini, Yoav and Daniel Yekutieli. 2005.
False Discovery Rate-Adjusted Multiple Confidence Intervals for
Selected Parameters.
Journal of the American Statistical Association 100 (Mar.): 71-81.
- Vuong, Quang H. 1989.
``Likelihood-ratio Tests for Model Selection and Non-nested Hypotheses.''
Econometrica 57 (2): 307-333.
- Leonard A. Stefanski and Dennis D. Boos, 2002.
The Calculus of M-Estimation.
The American Statistician 56 (1, Feb.): 29-38.
- White, Halbert. 1982.
Maximum Likelihood Estimation of Misspecified Models.
Econometrica 50 (1): 1-25.
- D. A. Freedman. 2006.
On the so-called ``Huber Sandwich Estimator'' and ``robust'' standard errors.
The American Statistician 60: 299-302.
- Peter McCullagh and John A. Nelder. 1989.
Generalized Linear Models. 2d ed. Chapman and Hall.
- McCullagh, Peter. 1983. Quasi-likelihood Functions.
Annals of Statistics 11 (Mar.): 59-67.
- partial identification and identification with missing covariates (Nov 18)
- Joel L. Horowitz and Charles F. Manski. 2000.
Nonparametric Analysis of Randomized Experiments with Missing Covariate and Outcome Data.
Journal of the American Statistical Association
95 (449, Mar): 77-84.
- Charles F. Manski and Elie Tamer. 2002.
Inference on Regressions with Interval Data on a Regressor or Outcome.
Econometrica
70 (2, Mar): 519-546.
- Rosa L. Matzkin. 2007.
Nonparametric Survey Response Errors.
International Economic Review 48 (4): 1411-1427.
- Charles F. Manski. 1990.
Nonparametric Bounds on Treatment Effects.
American Economic Review
80 (2, Papers and Proceedings): 319-323.
- Francesca Molinari. 2010.
Missing Treatments.
Journal of Business and Economic Statistics 28 (1): 82-95.
- Walter R. Mebane, Jr. and Paul Poast. 2013.
``Causal Inference without Ignorability: Identification with Nonrandom
Assignment and Missing Treatment Data.''
Political Analysis 21 (2): 233-251.
- Charles F. Manski. 1995.
Identification in the Social Sciences. Harvard UP.
- Charles F. Manski. 2003.
Partial Identification of Probability Distributions. Springer.
- Rosa L. Matzkin. 2007.
Nonparametric Identification.
In James J. Heckman and Edward E. Leamer, eds.,
Handbook of Econometrics volume 6B. North-Holland.
Pp. 5307-5368.
- causal identification norms (or dogmas), DAGs and selectivity (Nov 25)
- Thomas J. Rothenberg. 1971.
Identification in Parametric Models.
Econometrica 39 (May): 577-591.
- Judea Pearl. 1995.
Causal Diagrams for Empirical Research.
Biometrika 82 (4, Dec.): 669-688. (plus discussion, 688-710).
- Holland, Paul. 1986,
Statistics and Causal Inference.
Journal of the American Statistical Association 81: 945-961.
- Heckman, J. J. 1978. Dummy endogenous variables in a simultaneous equation system.
Econometrica 46: 931-959.
- Heckman, J. J. 1979. Sample selection bias as a specification error.
Econometrica 47: 153-161.
- Roger Bowden. 1973.
The Theory of Parametric Identification.
Econometrica 41 (Nov): 1069-1074.
- Franklin Fisher. 1976.
The Identification Problem in Econometrics. Krieger.
- Roger Bowden and Darrell Turlington. 1984.
Instrumental Variables. Cambridge UP.
- Judea Pearl. 2009.
Causality: Models, Reasoning and Inference, 2d ed. Cambridge UP.
Chapters 1-5.
- James M. Robins. 1999.
Association, Causation, and Marginal Structural Models.
Synthese 121: 151-179.
- David A. Freedman and Jasjeet S. Sekhon. 2010.
Endogeneity in Probit Response Models.
Political Analysis 18 (2): 138-150.
- James J. Heckman and Edward Vytlacil. 2005.
Structural Equations, Treatment Effects, and Econometric Policy Evaluation.
Econometrica 73 (3, May): 669-738.
- bounded influence estimation (Nov 25)
- Stefanski, Leonard A., Raymond J. Carroll, David Ruppert. 1986.
Optimally Bounded Score Functions for Generalized Linear Models with Applications
to Logistic Regression.
Biometrika 73 (Aug): 413-424.
- Western, Bruce. 1995.
Concepts and Suggestions for Robust Regression Analysis.
American Journal of Political Science 39 (3): 786-817.
- Mebane, Walter R., Jr., and Jasjeet S. Sekhon. 2004.
Robust Estimation and Outlier Detection for Overdispersed Multinomial
Models of Count Data.
American Journal of Political Science 48 (April): 392-411.
- Mebane, Walter R., Jr. 2010.
Fraud in the 2009 Presidential Election in Iran?
Chance 23 (Mar.): 6-15.
- Hampel, Frank R. and Peter J. Rousseeuw and Elvezio Ronchetti. 1981.
The Change-of-Variance Curve and Optimal Redescending M-Estimators.
Journal of the American Statistical Association 76 (Sep): 643-648.
- Croux, Christophe and Peter J. Rousseeuw and Ola Hossjer. 1994.
Generalized S-Estimators.
Journal of the American Statistical Association 89 (Dec): 1271-1281.
- paper presentations (Dec 2, 9)
Walter Mebane
2013-09-28