SOC 206 Survey and Demographic Methods II

W09

Akos Rona-Tas

Office: SSB 488

Phone: 534-4699

Office Hours: WF 12-1 

            or by appointment

Email: aronatas@ucsd.edu     

            In this course we will cover multivariate linear regression, and some of its extensions and at the end you will be introduced to the basics of network analsysis.  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 conceptual issues and will de-emphasize mathematical technicalities. We will be using SPSS for Windows, AMOS, LIMDEP and UCINet 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. Knoke and Bohrnstedt, Statistics for Social Data Analysis, there are two other books you will need.Tim Futing Liao, Interpreting Probability Models: Logit, Probit and Other Generalized Linear Models will complement the textbook. Ivan Szelenyi, Socialist Entrepreneurs serves as substantive example. 
            There are a few other articles for this course to read. Most of those are available through JSTOR.

            You will have four assignments all downloadable from the course website. 

http://weber.ucsd.edu/%7Earonatas/soc20602.html

            All of you will have to make two presentations of the four assignments.  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.

SCHEDULE

1st Week

LINEAR MODELS

Causation and the Logic of Multivariate Analysis

Review of Regression

Reading:  B&K, Ch. 6 & 7 & 8

Dawes, Faust and Meehl, Clinical versus Actuarial Judgment. Science Volume 243, Issue 4899 March 31, 1989, 1668-1674.

Application:

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.

Szelenyi, Ivan. 1988.  Socialist Entrepreneurs.  Madison: University of Wisconsin Press

Further Reading:

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

2nd Week

Model Building, Multiple Regression and Normal Equations

Application:

Szelenyi, Ivan. 1988.  Socialist Entrepreneurs.  Madison: University of Wisconsin Press

Slides for Week 2

Regression Assumptions

3^rd Week

STRUCTURAL EQUATION MODELS

Path-Analysis

Latent Variable Models

AMOS

1st Assignment due

Reading:

B&K. Ch. 11

Application:

O.D. Duncan, Path Analysis: Sociological Examples. AJS, vol. 72, 1966

Further Readings:

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

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

Path Analysis slides

4th Week

Latent Variable Models (continued)

Reading:

B&K. Ch. 12

Application:

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.

5^th Week
PROBABILITY MODELS

Dichotomous Dependent Variable

Logistic Regression (Logit) and Probit

2^nd Assignment due

Reading:

B&K, Chapter 9

Liao, Chapters 1, 2, 3

Application:

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: Explaining fit using log-likelihood

6th Week

Polytomous Dependent Variable

Multinomial Logit

Reading:

Liao, Chapter  6

Application:

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

7th Week
Ordered Logit

Reading:

Liao, Chapter 4,5,

Application:

Espenshade, Thomas J. And Haishan Fu, An Analysis of English-Language Proficiency Among U.S. Immigrants,  ASR, vol. 62, 1999 pp.288-305

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.

8th Week
NETWORK ANALYSIS

Network Data and Network Measures

3^rd Assignment due

Reading:
Hanneman, Robert A. and Mark Riddle.  2005.  Introduction to social network methods.  Riverside, CA:  University of California, Riverside. Ch.1-3, 6-7 http://www.faculty.ucr.edu/~hanneman/nettext/

Application:
Peter V. Marsden. Core Discussion Networks of Americans. ASR Vol. 52, No. 1. (Feb., 1987), pp. 122-131

Further Reading:
Knoke, David and  Song Yang, Social Network Analysis, Sage
Wasserman, S. and K. Faust, 1994, Social Network Analysis. Cambridge: Cambridge University Press.

Linton C. Freeman, See you in the Funny Papers: Cartoons and Social Networks, CONNECTIONS 23(1): 32-42 2000

TO DOWNLOAD THE NETWORK DATAFILES CLICK HERE!

First set of lecture slides

Second set of lecture slides

9th Week
Network Measures

Reading:
Hanneman, Robert A. and Mark Riddle.  2005.  Introduction to social network methods.  Riverside, CA:  University of California, Riverside. Ch. 10-12. http://www.faculty.ucr.edu/~hanneman/nettext/

Application:
Scott J. South; Dana L. Haynie. 2004. Friendship Networks of Mobile Adolescents, Social Forces Vol. 83, No. 1. (Sep), pp. 315-350.

Further Reading:
Hanneman&Riddle, Ch.18

Padgett, John F. and Christopher K. Ansell. 1993. Robust Action and the Rise of the Medici, 1400 1434. AJS, 98:1259-1319.

Third set of lecture slides

10th Week

Network Measures in Linear Models
Review

4th Assignment due

Reading:

Adrian E. Raftery. 2001. Statistics in Sociology, 1950-2000: A Selective Review, Sociological Methodology, Vol. 31. (2001), pp. 1-45.

A. Abbott, Transcending General Linear Reality. Sociological Theory, vol 6:2 1988

Assignments:

1^st  Assignment:

Three variable regression. 3D plot, residuals.

2^nd Assignment

Structural Equations

3^rd Assignment

Probability Models.

4^th Assignment

Network Analysis.

Final Paper:

            Construct multivariate models to test some hypothesis.  The paper should follow the ASR format, roughly, this outline:

Abstract

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

Conclusion

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 03/19/2009 11:00 am