SOC 206 Quantitative Methods II
Office: SSB 488
or by appointment
In this course we will cover multivariate linear regression, and some of its extensions. I assume that you have taken SOC 205 or an equivalent course, and you are familiar with simple regression analysis. The course will focus on causal models and conceptual issues, and it will de-emphasize mathematical technicalities. We will be using STATA for data analysis.
My goal is not to turn you into statisticians. I will consider my course a success if at the end of the course you will be competent users of these techniques, and fearless readers of articles and books using these statistical tools. I also hope that you will be able to discuss critically and intelligently quantitative works from the discipline.
Apart from the textbook. Agresti
and Finlay, Statistical Methods for the Social Sciences, there is one
other book you will need. Tim Futing Liao, Interpreting
Probability Models: Logit, Probit and Other
Generalized Linear Models. The books are available in the mailroom of the
There are a few other articles for this course to read. Most of those are available through JSTOR or other electronic databases you can access through the library.
We have three thematic parts (linear regression models, structural equation models and probability models) broken up into nine two day segments. The items in the Reading section must be completed before the first date of the segment and the items in the Application section before the second date.
You will have four assignments all downloadable from the course website.
All of you will have to make two presentations. One will be one of your assignments that you have to present at the seminar before it is due. The second is a presentation of one of the articles from the Application section that has an *. There is a final research paper where you test some theory using multivariate analysis. Each assignment will count as 15% of your grade and the final paper will count for 30%, class participation including the presentations will make up the rest.
January 5, 7
Causation and the Logic of Multivariate Analysis
Review of OLS Regression
Reading: A&F, Ch. 9, 10, 11
Dawes, Faust and Meehl, Clinical versus Actuarial Judgment. Science Volume 243, Issue 4899 March 31, 1989, 1668-1674.
Lave, Charles A. and James G. March. An Introduction to Models in the Social Sciences. Chapter 1,2 (copies available in the mailroom)
The Great Chocolate Debate
Maurage, Pierre, Alexandre Heeren, and Mauro Pesenti. Does Chocolate Consumption Really Boost Nobel Award Chances? The Peril of Over-Interpreting Correlations in Health Studies. The Journal of Nutrition, April 24, 2013
The Rossi - Zeisel Debate
Berk, Richard A., Kenneth J. Lenihan, and Peter H. Rossi. Crime and Poverty: Some Experimental Evidence from Ex-Offenders. ASR. Vol.45. No.5. pp.766-786.
Zeisel, Hans. Disagreement over the Evaluation of a Controlled Experiment. AJS. Vol.88. No.2. pp.378-389.
Rossi, Peter H., Richard A. Berk and Kenneth J. Lenihan. Saying It Wrong with Figures: A Comment on Zeisel. AJS Vol.88. No.2. pp.390-393.
Zeisel, Hans. Hans Zeisel Concludes the Debate. AJS. Vol.88. No.2. pp.394-396.
Dawes, Robyn. 1979. The Robust Beauty of Improper Linear Models in Decision Making. American Psychologist, July, pp.571-582
H.M. Blalock, Causal Inferences in Nonexperimental Research.
H. Smith, Specification Problems in Experimental and Nonexperimental Social Research, In Sociological Methodology 1990, 20:59-91.
Reading : A&F, Ch. 9, 10, 11
Berk, Richard A. An Introduction to Sample Selection Bias in Sociological Data, ASR vol. 48, 1983
Winship, Christopher and Robert Mare. Models for Sample Selection Bias. Annual Review of Sociology, Vol. 18 (1992), pp. 327-350
Ross M. Stolzenberg and Daniel A. Relles. Tools for Intuition about Sample Selection Bias and Its Correction. ASR, Vol. 62, No. 3 (1997), pp. 494-507
Antonakis, John and Samuel Bendahan, Philippe Jacquart, Rafael Lalive. On making causal claims: A review and recommendations. The Leadership Quarterly 21 (2010) 1086–1120 (A short and simplified version of this article is presented here with some cheesy animation by Antonakis https://www.youtube.com/watch?v=CCiIfjm8qjw .)
Gerber, Theodore. Membership Benefits or Selection Effects? Why Former Communist Party Members Do Better in Post-Soviet Russia. Social Science Research, 2000, pp. 25–50
Rona-Tas, Akos and Alya Guseva. The Privileges of Past Communist Party Membership in Russia and Endogenous Switching Regression. Social Science Research, 2001, pp. 641-652
January 19 Martin Luther King Day
January 21, 26
Generalized Linear Models
Non-linearity, non-additivity, heteroscedasticity, count data,
January 28, February TBD
STRUCTURAL EQUATION MODELS
Latent Variable Models
1st Assignment due January 28
Otis Dudley Duncan, Path Analysis: Sociological Examples. AJS, vol. 72, 1966
*Prudence A. Widlak and Carolyn C. Perrucci, Family Configuration, Family Interaction, and Intellectual Attainment, Journal of Marriage and Family, Vol. 50, No. 1 (Feb., 1988), pp. 33-44
O.D. Duncan, Introduction to Structural Equation Models.
P.M. Blau and O.D. Duncan, The American Occupational Structure.
February TBD, February 9
Latent Variable Models (continued)
Erin. 2007. Not by Productivity Alone: How Visibility and
Specialization Contribute to Academic Earnings, ASR vol 72, (August) pp.533-561
*David, John Frank, John W. Meyer and David Miyahara. 1995. The Individualist Polity and the Prevalence of Professionalized Psychology: A Cross-National Study. ASR vol.60 (June) pp.360-377
John C. Loehlin, Latent Variable Models: An Introduction to Factor, Path, and Structural Analysis.
Bollen, Kenneth A.. Structural equations with latent variables.
February 16 Presidents’ Day
February 11, 18
Dichotomous Dependent Variable
Logistic Regression (Logit) and Probit
2nd Assignment due February11
A&F, Chapter 15
Liao, Chapters 1, 2, 3
*Rona-Tas, Akos. 1994. The First Shall Be Last? American Journal of Sociology 100/1:40-69
Long, J. Scott. 1997. Regression Models for Categorical
and Limited Dependent Variables.
February 23, 25
Polytomous Dependent Variable
Liao, Chapter 6
*Tak Wing Chan and John H. Goldthorpe, Social Status and Newspaper Readership' The American Journal of Sociology, Vol. 112, No. 4 (Jan., 2007), pp. 1095-1134
March 2, 4
3rd Assignment due March 2
Liao, Chapter 4,5,
*Cech, Erin , Brian Rubineau, Susan Silbey and Caroll Seron. 2011. Professional Role Confidence and Gendered Persistence in Engineering. American Sociological Review, 76/5 pp. 641-666
C. Winship and R.D. Mare, Regression Models with Ordinal Variables, ASR, 1984 August, 49:512-525.
Allison, Discrete-time Methods
for the Analysis of Event Histories, in
Yamaguchi, Kazuo, Event History Analysis,
March 9, 11
4th Assignment due March 11
Charles Tilly. 2008. Why? What Happens When People Give Reasons... and Why. Princeton UP
Adrian E. Raftery. 2001. Statistics in Sociology, 1950-2000: A Selective Review, Sociological Methodology, Vol. 31. (2001), pp. 1-45.
Andrew Abbott, Transcending General Linear Reality. Sociological Theory, vol 6:2 1988
Three variable regression. Plot, residuals.
Data Analysis for Final Paper.
Construct multivariate models to test some hypothesis. The paper should follow the ASR format, roughly, this outline:
Introduction that states the problem
Literature review reflecting some familiarity with the literature outlining alternative theories
Your own theory and the derived hypotheses
Data and Method
Discussion of Findings
References (ASR format)
The paper should be 15- 25 pages in length without the tables and the references. Please use a 12 point font, double-space and number each page and submit the paper as an e-mail attachment.
Final Paper Due 03/20/2015 12:00 am