Graduate School for Social Research, Polish Academy of Sciences
Advanced Quantitative Methods in Comparative Social Sciences
Syllabus 2012 – 2013
Instructors: Dr. Irina Tomescu-Dubrow and Prof. Kazimierz M. Słomczyński
Time & Place: Wednesdays: 12:30 – 1:45 (Room 242, Lecture) and 2:00-3:30 (Room 124, Lab)
Course Website: https://statisticalmethods.wordpress.com/
Office Hours: Wednesdays 16:00 – 17:00, Room 211, and by appointment
This course is designed for students who have a background in quantitative methods for the social sciences. Students should be familiar with descriptive statistics, testing differences between two and more means, and OLS regression analysis.
Basic outline of the course:
Linear Regression and Correlation – Review
Multiple Regression and Correlation
Model Building with Multiple Regression
Exploratory and Confirmatory Factor Analysis
Structural Equation Modeling
This course will feature a series of lectures and lab sessions.
This course aims to teach students the logic and the theoretical assumptions behind some of the main techniques in advanced statistics for the social sciences, and how these techniques are applied to testing specific hypotheses. Students will learn to interpret empirical results, and to make critical evaluations of published social research that employs the methods covered in class. We will apply STATA routines to two data sets: ESS-CON and POLPAN. ESS-CON is the European Social Survey data with additional variables characterizing countries (allowing researchers to perform cross-national comparisons); POLPAN is the Polish Panel Survey conducted in 1988-2008 (allowing researchers to perform historical comparisons).
1. Alan Agresti and Barbara Finlay. Statistical Methods of the Social Sciences. 3rd edition. Prentice Hall.
2. Tabachnick, B. G., & Fidell, L. S. (2007). Using Multivariate Statistics, 5th ed. Boston: Allyn and Bacon.
Course Requirements and Evaluation:
Class participation (15%): Students are expected to discuss all of the assigned readings on the due date and to participate in in-class discussions and projects.
Two Assignments (15% each; 30% total): Assignments, to be distributed during the course, will require analyses and interpretation of statistical results from software output. While studying with another student is permitted and even encouraged, you need to write the answers in your own words.
Term Paper (55%): Each student is expected to choose a substantive topic and apply appropriate statistical techniques to write a paper that could be an initial version for publishable work. The topics will be discussed during individual consultations.
|A 94-100||B+ 87-89||C+ 77-79||D+ 65-69||E (Failure) 59-0|
|A- 90-93||B 84-86||C 74-76||D 60-64|
|B- 80-83||C- 70-73|
Policies on Attendance, Late Materials, and Make-Ups:
We expect everyone to show up to class on time. During class, cell phones and other electronic devices with noise-capacity must be turned off. We will make exceptions to this rule if you explain why you need them turned on during class; you have to inform us of this reason before class begins.
Assignments are to be turned in electronically, via email (firstname.lastname@example.org) by the specified deadline. We accept late materials only if notified 24 hours prior to the deadline.
While working together on assignments is encouraged, you need do your own write-up. Identical assignments will result in failing grade.
For emailed assignments: it is the responsibility of the student to be sure that the instructor receives it.
Course Outline and Course Readings
Readings marked with an “R” are REQUIRED, or mandatory readings. Those with “OP” are optional or non-mandatory readings. Students are expected to have read at least the REQUIRED readings on the date they are assigned.
|October 10||Organizational meeting. Linear Regression and Correlation||OP – Agresti and Finlay, Ch. 4 & 9OP – Tabachnick and Fidell, Ch. 1 (Introduction)|
|October 17||Multiple Regression and Correlation – Part I||R – Tabachnick and Fidell, Ch. 4 (Cleaning Up Your Act) & 5 (Multiple Regression)OP– Agresti and Finlay, Ch. 10|
|October24||Multiple Regression and Correlation – Part II||R – Tabachnick and Fidell, Ch. 5 (Multiple Regression)R – Tomescu-Dubrow, Irina and Henryk Domanski (2010)“How to Model Parental Education Effects On Men And Women’s Attainment? Cross-National Assessments of Different Approaches.” ASK: Society, Research, Methods 19: 21-50.
OP – Agresti and Finlay, Ch. 11
|November 7||Model Building with Multiple Regression(Logistic)||R – Agresti and Finlay, Ch. 14R – Tabachnick and Fidell, Ch. 12 (Logistic)|
|November 7||1st Assignment Due by 6 PM via email (email@example.com)|
|November 14||Exploratory and Confirmatory Factor Analysis – Part I||R – Tabachnick and Fidell, Ch. 13 (Principal Components and Factor Analysis)|
|December 5||Exploratory and Confirmatory Factor Analysis – Part II||R – Joanne Miller, Kazimierz M. Slomczynski and Ronald J. Schoenberg. 1981. “Assessing Comparability of Measurement in Cross-National Research: Authoritarian-Conservatism in Different Sociocultural Settings.” Social Psychology Quarterly44(3): 178-191R – Tabachnick and Fidell, Ch. 13 (Principal Components and Factor Analysis)
|December 19||Structural Equation Modeling – Part I||R – Tabachnick and Fidell, Ch. 14 (Structural Equation Modeling)|
|January 9||Structural Equation Modeling – Part II||R – Kazimierz M. Slomczynski, Joanne Miller and Melvin L. Kohn. 1981.Stratification, Work, and Values: A Polish-United States Comparison American Sociological Review. 46(6): 720-744|
|January 14||2nd Assignment Due by 6 PM, via email (firstname.lastname@example.org)|
|January 16||Multi-Level Modeling, Part I||R – Tabachnick and Fidell, Ch. 15 (Multilevel Linear Modeling)|
|January 23||Multi-Level Modeling, Part II||R – Tabachnick and Fidell, Ch. 15 (Multilevel Linear Modeling)R – Dubrow, Joshua Kjerulf, Kazimierz M. Slomczynski and Irina Tomescu-Dubrow. 2008. “Effects of Democracy and Inequality on Soft Political-Protest in Europe: Exploring the European Social Survey Data.” International Journal of Sociology 38(3):36-51.|
|January 25||Term Paper Due by 6 PM via email (email@example.com)|