SOC 206 Quantitative Methods II


Akos Rona-Tas

Office: SSB 488

Phone: 534-4699

Office Hours:

MW 11:30-12:20 

            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 Sociology Dept. 
            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

Messerli, Franz. Chocolate Consumption, Cognitive Function, and Nobel Laureates. The New England Journal of Medicine 2012; 367:1562-1564, October 18  ( )

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.


Further Reading:

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.




Slides for Week 1


January 12,14

Model Building , Selection Bias, Multiple OLS Regression and Normal Equations


Reading : A&F, Ch. 9, 10, 11

Berk, Richard A. An Introduction to Sample Selection Bias in Sociological Data, ASR vol. 48, 1983



*P. Sharkey and F. Elwert, The Legacy of Disadvantage: Multigenerational Neighborhood Effects on Cognitive Ability. AJS, May 2011


Further Reading:

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 .)

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



Slides for Week 2

Regression Assumptions

January 19 Martin Luther King Day


January 21, 26

Generalized Linear Models

Non-linearity, non-additivity, heteroscedasticity, count data,


Reading: A&F Ch 14



*Kornrich, S., et al. 2013. Egalitarianism, Housework, and Sexual Frequency in Marriage. ASR, February

*Uzzi, Brian. 1996. The Sources and Consequences of Embeddedness for the Economic Performance of Organizations: The Network Effect. ASR, August




January 28, February TBD 



Latent Variable Models


1st Assignment due January 28


A&F pp.527-541



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


Further Readings:

O.D. Duncan, Introduction to Structural Equation Models.

P.M. Blau and O.D. Duncan, The American Occupational Structure.


Path Analysis slides

February TBD, February 9

Latent Variable Models (continued)



A&F pp.527-541


*Leahey,  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



Further Readings:

John C. Loehlin, Latent Variable Models: An Introduction to Factor, Path, and Structural Analysis.

Bollen, Kenneth A.. Structural equations with latent variables.


Structural Equation Models with Latent Variables slides



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



Further Reading:

Long, J. Scott. 1997. Regression Models for Categorical and Limited Dependent Variables. Thousand Oaks, CA: Sage


Output 1: Introducing Logistic Regression


Output 2: Explaining fit using log-likelihood


February 23, 25

Polytomous Dependent Variable

Multinomial Logit



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

A. Rona-Tas and J. Borocz, The Formation of New Business Elites in Bulgaria, the Czech Republic, Hungary and Poland:  Continuity and Change, Pre-Communist and Communist Legacies.




Output: Multinomial and ordered logit  


March 2, 4
Ordered Logit


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


Further Reading:

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 S. Leinhard ed. Sociological Methodology, 1982, San Francisco: Jossey-Bass

Yamaguchi, Kazuo, Event History Analysis, Newbury Park: Sage 1991.



March 9, 11



4th Assignment due March 11


John P. A. Ioannidis. 2005. Why Most Published Research Findings Are False. PLoS Med 2(8): e124. doi:10.1371/journal.pmed.0020124

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




1st  Assignment:

Three variable regression. Plot, residuals.

2nd Assignment

Structural Equations

3rd Assignment

Probability Models.

4th Assignment

Data Analysis for Final Paper.

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