Sociology 229: Topics in Advanced Regression Models
Fall 2020, Class Code: 69765
Time & Place: Wednesday 2:00-4:50
Instructor: Evan Schofer
Office Hours: Thursday 1:30-2:30
Office hours zoom link: https://uci.zoom.us/j/96176670197 (Links to an external site.)
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.
Readings
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.
Many of the readings are available online via Canvas.
The course will draw heavily on readings from the following texts:
Long, J. Scott and Jeremy Freese. 2014. Regression Models for Categorical Dependent Variables Using Stata, Third Edition. Stata Press. ISBN: 978-1-59718-111-2
Cleves, Mario, William W. Gould, Roberto G. Gutierrez, and Yulia Marchenko. 2016. An Introduction to Survival Analysis Using Stata, 3rd Edition. Stata Press. ISBN: 978-1-59718-174-7
Rabe-Hesketh, Sophia and Anders Skrondal. 2012. Multilevel and Longitudinal Modeling Using Stata, Third Edition. Stata Press. ISBN: 978-1-59718-108-2
These books are very good, and useful to have around. But, depending on your interests and finances, you can certainly get through the course with a borrowed copy. Older editions would also work.
Stata Software
We will be using the statistical software package Stata. You may also purchase Stata via UCI’s Office of Information Technology (OIT). Stata is also available in some computer labs on campus. You may use other software (such as R) to complete the assignments, if you prefer, but I don’t have sample code and won’t always be able to provide debugging assistance.
Assignments and Evaluation
Course assignments and handouts are available online (see link at top of web page).
Short Assignments. There will be five 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; numerically graded assignments decrease by one point) per day past the due date. Extensions will be granted for legitimate reasons if requested in advance.
Your final grade will be computed based on the percentage weightings indicated. I typically apply a curve to raise the grade distribution. 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
NOTE: I may occasionally make minor changes to the reading assignments. Any changes will be small and made well in advance of their due date.
Fall 2020: Oct 1-Dec 11, Holidays on Nov 11, Nov 26, Nov 27.
Class meetings: Oct 7, Oct 14, Oct 21, Oct 28, Nov 4, Nov 11, Nov 18, Nov 25, Dec 2, Dec 9.
Week 1: Introduction and Review (Oct 7)
*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. 2014. “Introduction to Stata.” Chapter 2 in Regression Models for Categorical Dependent Variables Using Stata (Third Edition). College Station, TX: Stata Press.
Additional helpful Stata information can be found here:
http://www.ats.ucla.edu/stat/stata/ (Links to an external site.)
http://www.cpc.unc.edu/services/computer/presentations/statatutorial (Links to an external site.)
*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. 2013. “Union Membership and Political Participation in the United States.” Social Forces.
Week 2: Multinomial Logistic Regression (Oct 14)
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 (Oct 21)
Long, J. Scott and Jeremy Freese. “Models for Count Outcomes.” Chapter 9 in Regression Models for Categorical Dependent Variables Using Stata (Third 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: Multilevel Models (Oct 28)
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:
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 5: Multilevel and Panel Models (Nov 4)
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:
Ready, Douglas D. 2010. “Socioeconomic Disadvantage, School Attendance, and Early Cognitive Development: The Differential Effects of School Exposure.” Sociology of Education, 83, 4:271-286.
Week 6: Veteran’s Day: NO CLASS MEETING.
Week 7: Panel and Time-Series Cross-Section Models (Nov 18)
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 7: Event History Analysis 1 (Nov 25)
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 8: Event History Analysis 2 (Dec 2)
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.”
- Chapter 12 (focus on section 12.1) “Parametric Models.”
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.
*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 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 10: Causal Inference (Dec 9)
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
- *Chapter 3: Making Regression Make Sense
- *Chapter 4: Instrumental Variables in Action
- *Chapter 5: Parallel Worlds: Fixed Effects, Differences in Differences, and Panel Data
- *Chapter 6: Getting a Little Jumpy: Regression Discontinuity
Gelman, Andrew and Jennifer Hill. 2006. “Data Analysis Using Regression and Multilevel/Hierarchical Models.” Cambridge University Press.
- Chapter 9: Causal Inference Using Regression on the Treatment Variable.
- Chapter 10: Causal Inference Using Advanced Models
Morgan, Stephen L. and Christopher Winship. 2007. Counterfactuals and Causal Inference. Cambridge University Press.
- Chapter 1: Introduction
- *Chapter 2: The Counterfactual Model
- *Chapter 3: Estimating Causal Effects by Conditioning
- *Chapter 4: Matching Estimators of Causal Effects
- *Chapter 7: Instrumental Variables of Causal Effects
- *Chapter 9: Repeated Observations and Causal Effects