Course Information

1. Basic course 
“The Factorial Survey: An Introduction”

Instructor: prof. Hermann Dülmer (University of Cologne).

Objectives: The course on Factorial Research Design will be relevant for young social science researchers from different countries. The factorial survey (vignette analyses) is one of the experimental methods in social sciences for theory testing. Since the experiment design is integrated into the questionnaire, respondents have to evaluate a set of objects, persons or situations. Different characteristics from this set are taken into account. By evaluating the responses of respondents the researcher is able to reveal which of the characteristics is important to the individual. This method is crucial for comparative social research, as it allows comparison of different groups of people. The course consists of theoretical and practical parts.

Syllabus:

Theoretical Part: Lectures

1.    Experiments in Social Sciences (Basic Ideas of Experiments)

2.    Generating Vignettes: Selection of Levels and Dimensions

3.    Generating Vignettes: Random and Quota Designs

4.    Selecting an Answer Scale

Practical Part: Workshops

1.    Selecting an Own Research Topic, Deriving Hypotheses

2.    Constructing and Discussing the Generated Vignettes

3.    Short Pretesting of the Factorial Survey

4.    Analysis of  Factorial Surveys (Multilevel Analysis)

2. Additional course
“Data visualization in R”

(!) Information to prepare for the course:   R installation manuals.pdf

Instructors: Boris Sokolov (PhD, LCSR, HSE) and Veronica Kostenko (LCSR, HSE)

Objectives: Data visualization is an important analytic tool for social scientists. It may help understand patterns behind the data at the exploratory stage of analysis and present the main findings in a clear and convincing way. Overall patterns and data structure can be best accessed using the methods of visualization. The main goal of this course is to provide an introduction to graphical capacities of R, one of the most popular languages of statistical programming.

Syllabus:

1. Introduction to R Graphics

2. Reproducing basic R graphics using package ggplot2

3. Customizing plots in ggplot2

4. Visualizing complex statistical models

5. Advanced R graphics: maps, 2D histograms, 3D plots

3. Key-lectures on cross-national research 

Lecturer: prof. Ronald Inglehart (University of Michigan, LCSR HSE)

Topics to be annouced later...