Sociology 229:  Topics in Advanced Regression Models

 

Winter 2012, Class Code: 69770

 

Time/Place:

Tuesday 9:00-11:50am, SSPB 2214

Class Web Page:

http://www.socsci.uci.edu/~schofer/2012soc229AR/home229AR.htm

 

 

Instructor:

Evan Schofer

Office:

SSPB 4271

Office Hours

Tuesday 12:00-1:00pm and by appointment

Office Phone:

(949) 824-1397

Email:

schofer at uci dot edu

 

Introduction

 

The purpose of this course is to provide a broad survey of a large number of useful statistical tools for social scientists, including multinomial logistic regression, count models, event history/survival analysis, multilevel models, and models for panel data.  The intent is to provide an overview of many different techniques, rather than going into great depth on any particular topic. 

 

Readings

 

Readings can be found online via the UCI Webfiles system.  Additionally, you may receive handouts and other short reading assignments.  Complete reading assignments prior to the class in which material will be covered.  You will get much more out of class if you have already finished the readings. 

 

Online readings can be accessed via the following web link:  http://webfiles.uci.edu/schofer/classes/2012soc229AR

NOTE:  UCInet ID and password required.  If you have never used webfiles before, you must register at webfiles.uci.edu to gain access.

 

Stata Software

 

We will be using the statistical software package Stata.  It is available on machines in the computer labs in the Social Science Tower (SST 170 and SST 604).  You may also purchase Stata via UCI’s Office of Information Technology (OIT).

 

Assignments and Evaluation

 

Short Assignments.  There will be six short assignments, collectively worth 90% of your final grade.  Most are brief exercises involving Stata, others require some writing.

 

Class Participation.  You are expected to attend class regularly and contribute to class discussion.  Class participation will count for 10% of your final grade.

 

This course does not have a miderm or final exam.

 

Assignments received late will be marked down one partial grade (i.e., and A becomes an A-, C+ becomes a C) per day past the due date.  Extensions will be granted for legitimate reasons if requested in advance – before the due date. 

 

Your final grade will be computed based on the percentage weightings indicated.  In the event of a borderline grade, I may use my discretion in adjusting grades based on course participation, improvement, and effort (or lack thereof).  Incompletes will not be given, except in unusual circumstances.

 

Schedule & Reading Assignments

 

* indicates optional reading

 

Week 1:  Introduction and Review  (January 10)

 

*Angrist, Joshua D. and Jorn Steffen Pischke.  2009.  Mostly Harmless Econometrics:  An Empiricists Companion.  Princeton, NY:  Princeton University Press.

  • Chapter 1:  Questions About Questions
  • Chapter 2:  The Experimental Ideal

 

*Long, J. Scott and Jeremy Freese.  2006.  “Introduction to Stata.”  Chapter 2 in Regression Models for Categorical Dependent Variables Using Stata (Second Edition).  College Station, TX:  Stata Press.

 

Additional helpful Stata information can be found here:

http://www.ats.ucla.edu/stat/stata/

http://www.cpc.unc.edu/services/computer/presentations/statatutorial

 

*Long, J. Scott and Jeremy Freese.  2006.  “Models for Binary Outcomes.”  Chapter 4 in Regression Models for Categorical Dependent Variables Using Stata (Second Edition).  College Station, TX:  Stata Press.

 

Empirical Example: 

 

*Kerrissey, Jasmine and Evan Schofer.  Forthcoming.  “Union Membership and Political Participation in the United States.”  Social Forces. 

 

 

Week 2:  Multinomial Logistic Regression  (January 17)

 

Long, J. Scott and Jeremy Freese.  2006.  “Models for Nominal Outcomes With Case Specific Data.”  Chapter 6 in Regression Models for Categorical Dependent Variables Using Stata (Second Edition).

 

Empirical Examples: 

 

McVeigh, Rory and Christian Smith.  1999.  “Who Protests in America:  An Analysis of Three Political Alternatives – Inaction, Institutionalized Politics, or Protest.”  Sociological Forum, 14, 4:685-702. 

 

Mullen, Ann L., Kimberly A. Goyette, and Joseph A. Soares.  2003.  “Who Goes to Graduate School?  Social and Academic Correlates of Educational Continuation After College.”  Sociology of Education, 76,2:143-169.

 

*Gerber, Theodore P.  2000.  “Market, State, or Don’t Know?  Education, Economic Ideology, and Voting in Contemporary Russia.”  Social Forces, 79, 2:477-521.

 

 

Week 3:  Count Models  (January 24)

 

Short Assignment #1 Due.

 

Long, J. Scott and Jeremy Freese.  2006.  “Models for Count Outcomes.”  Chapter 8 in Regression Models for Categorical Dependent Variables Using Stata (Second Edition).

 

Empirical Examples: 

 

Cole, Wade.  2006.  “Accrediting Culture:  An Analysis of Tribal and Historically Black College Curricula.”  Sociology of Education, 79:355-388.

Haynie, Dana L.  2001.  “Delinquent Peers Revisited: Does Network Structure Matter?”  American Journal of Sociology, 106, 4:1013-1057.

 

*Isaac, Larry and Lars Christiansen.  2002.  “How the Civil Rights Movement Revitalized Labor Militancy.”  American Sociological Review, 67:722-746.

 

 

Week 4:  Event History Analysis 1  (January 31)

 

Short Assignment #2 Due.

 

Cleves, Mario, William W. Gould, and Roberto Gutierrez.  2004.  An Introduction to Survival Analysis Using Stata, Revised Edition.  Stata Press.

  • Chapter 1 “The Problem of Survival Analysis.”
  • Chapter 2 (focus on section 2.3), “Describing the Distribution of Failure Times.” 
  • Chapter 4 “Censoring and Truncation.” 
  • Chapter 5 “Recording Survival Data.” 
  • *Chapter 8 “Nonparametric Analysis.” 

 

Hironaka, Ann M.  2005.  “World Patterns in Civil War Duration.”  Chapter 2 in Neverending Wars.  Cambridge, MA:  Harvard University Press.

 

* Box-Steffensmeier, Janet M. and Bradford Jones.  2004.  Event History Modeling:  A Guide for Social Scientists.  Cambridge, UK:  Cambridge University Press.

  • Chapter 1 “Event History and Social Science.” 
  • Chapter 2 “The Logic of Event History Analysis.”

 

 

Week 5:  Event History Analysis 2  (February 7)


Short Assignment #3 Due.

 

Cleves, Mario, William W. Gould, and Roberto Gutierrez.  2004.  An Introduction to Survival Analysis Using Stata, Revised Edition.  Stata Press.

  • Chapter 3.  “Hazard Models.”
  • Chapter 9 (section 9.1 only), “The Cox Proportional Hazards Model.”
  • Chapter 10 “Model Building Using stcox.” 

 

Box-Steffensmeier, Janet M. and Bradford Jones.  2004.  Event History Modeling:  A Guide for Social Scientists.  Cambridge, UK:  Cambridge University Press.

  • Chapter 5 “Models for Discrete Data.”

 

Empirical Example: 

 

Soule, Sarah A and Susan Olzak.  2004.  “When Do Movements Matter? The Politics of Contingency and the Equal Rights Amendment.”  American Sociological Review, Vol. 69, No. 4. (Aug., 2004), pp. 473-497.

 

 

Week 6:  Event History Analysis 3 (February 14)

 

Cleves, Mario, William W. Gould, and Roberto Gutierrez.  2004.  An Introduction to Survival Analysis Using Stata, Revised Edition.  Stata Press.

  • Chapter 11  “The Cox Model:  Diagnostics.”
  • Chapter 12 (focus on section 12.1) “Parametric Models.”
  • Chapter 13 (focus on 13.0, 13.1.1, 13.2.1) “A Survey of Parametric Regression Models in Stata.” 

 

Long, J. Scott, Paul D. Allison, and Robert McGinnis.  1993.  “Rank Advancement in Academic Careers:  Sex Differences and the Effects of Productivity.”  American Sociological Review, 58, 5:703-722.

 

*Schofer, Evan.  2003.  “The Global Institutionalization of Geological Science, 1800-1990.”  American Sociological Review, 68 (Dec): 730-759.

 

Week 7:  Multilevel Models  (February 21)

 

Short Assignment #4 Due.

 

Raudenbush, Stephen W. R and Anthony S. Bryk.  2002.  “Introduction.”  Chapter 1 in Hierarchical Linear Models:  Applications and Data Analysis Methods.  Thousand Oaks, CA:  Sage.

 

Raudenbush, Stephen W. R and Anthony S. Bryk.  2002.  “Applications in Organizational Research.”  Chapter 5 in Hierarchical Linear Models:  Applications and Data Analysis Methods.  Thousand Oaks, CA:  Sage.

 

Rabe-Hesketh, Sophia and Anders Skrondal.  Multilevel and Longitudinal Modeling Using Stata.  College Station, TX:  Stata Press.

  • Chapter 1, Sections 1-1.4
  • Chapter 2

 

Empirical Example: 

 

TBA

 

 

Week 8:  Multilevel and Panel Models (February 28)

 

Tabanchick, Barbara G. and Linda S. Fidell.  “Multilevel Linear modeling.”  2007.  Chapter 15 in Using Multivariate Statistics (fifth edition).  Boston, MA:  Pearson.

 

Kennedy, Peter.  2003.  A Guide to Econometrics (5th Ed).  Cambridge, MA:  MIT Press.

  • Chapter 17:  Panel Data.

 

Empirical Example:

 

Schofer, Evan and Marion F. Gourinchas.  2001.  “The Structural Contexts of Civic Engagement:  Voluntary Association Membership in Comparative Perspective.”  American Sociological Review, 66 (Dec): 806-828.

 

 

Week 9:  Panel and Time-Series Cross-Section Models (March 6)

 

Short Assignment #5 Due.

 

Baltagi, Badi H.  2008.  Econometric Analysis of Panel Data (4th Ed).  John Wiley and Sons.

  • Chapter 1:  Introduction.
  • Chapter 2:  One-Way Error Component Regression Model.

 

Beck, Nathaniel.  2001.  “Time-Series Cross-Section Data:  What Have We Learned in the Past Few Years?”  Annual Review of Political Science, 4:271-293.

 

Schofer, Evan and Wesley Longhofer.  2011.  “The Structural Sources of Associational Life.”  American Journal of Sociology.

 

*Beck, Nathaniel and Jonathan N. Katz.  2009.  “Modeling Dynamics in Time-Series Cross-Section Political Economy Data.”  California Institute of Technology:  Social Science Working Paper 1304. 

 

*Beck, Nathaniel.  2006.  “Time-Series Cross-Section Methods.”  Working Paper.

 

*Woolridge, Jeffrey M.  2009.  Introductory Econometrics:  A Modern Approach.  Mason, OH:  South-Western.

  • Chapter 13.  Pooling Cross-Sections Across Time:  Simple Panel Data Methods.
  • Chapter 14.  Advanced Panel Data Methods.

 

*Angrist, Joshua D. and Jorn Steffen Pischke.  2009.  Mostly Harmless Econometrics:  An Empiricists Companion.  Princeton, NY:  Princeton University Press.

  • Chapter 5:  Parallel Worlds:  Fixed Effects, Differences-in-Differences, and Panel Data.

 

*Baltagi, Badi H.  2008.  Econometric Analysis of Panel Data (4th Ed).  John Wiley and Sons.

  • Chapter 8:  Dynamic Panel Data Models

 

*Woolridge, Jeffrey M.  2004.  Econometric Analysis of Cross Section and Panel Data.  Cambridge, MA:  MIT Press.

 

 

Week 10:  Miscellaneous Topics & Wrap up  (March 13)

 

Short Assignment #6 Due.

 

Week 10 readings subject to change.  (Changes will be announced well in advance.)

 

Penner, Andrew and Marcel Paret.  2007.  “Gender Differences in Mathematics Achievement:  Exploring the Early Grades and the Extremes.”  Social Science Research, 37:239-253.

 

Grodsky, Eric, John Robert Warren, and Demetra Kalogrides.  2009.  “State High School Exit Examinations and NAEP Long-Term Trends in Reading and Mathematics, 1971-2004.  Educational Policy, 23:589-614.

 

Field, Andy.  2000.  “Exploratory Factor Analysis.”  Chapter 11 in Discovering Statistics Using SPSS for Windows:  Advanced Techniques for the Beginner.  London, UK:  Sage.