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Member rate £492.50
Non-Member rate £985.00
Save £45 Loyalty discount applied automatically*
Save 5% on each additional course booked
*If you attended our Methods School in Summer/Winter 2024.
Monday 14 ꟷ Friday 18 February 2022
Minimum of 2 hours of live teaching per day
09:30 ꟷ 12:30 CET
VIR: This is a virtual course
This course provides a highly interactive online teaching and learning environment, using state of the art online pedagogical tools. It is designed for a demanding audience (researchers, professional analysts, advanced students) and capped at a maximum of 16 participants so that the teaching team can cater to the specific needs of each individual.
The course offers an introduction to the main statistical techniques used to analyse cross-national comparative surveys data.
Its main goal is to teach you how different statistical methods treat the ‘country effect’: how statistical models (linear regression, logit models, loglinear models, multilevel regression models), scaling techniques (from simple methods to complex factorial techniques) or data reduction methods (factor and PCA analysis) test for the ‘invariance’ of the relationship between variables across countries.
The course has two key points:
3 credits Engage fully with class activities
4 credits Complete a post-class assignment
Bruno Cautrès is attached to CEVIPOF – Centre de recherches politiques de Sciences Po (Paris), at the Fondation Nationale des Sciences Politiques in Paris.
He is a senior CNRS research fellow with interests in voting behaviour, political attitudes and behaviours, comparative survey research and quantitative techniques.
Bruno is involved in a variety of projects, including the European Social Survey, European Values Studies, International Social Survey Programme and European elections studies; and he participates in the development of elections studies in France. His current research programme concerns political trust and attitudes to democracy in France.
We start with a review of the substantial and methodological problems the multivariate statistical analysis tries to solve for comparing countries, particularly what is a ‘country effect’ and how this translates in statistical terms. The first day’s activities will also show very simple recalls using descriptive and bivariate techniques applied to ‘country effects’ problems.
Then we will work to understand the two main types of multivariate techniques, still applied to the same question of ‘country effects’:
Finally, on the Friday, we will also extend the perspective to multilevel analysis applied to cross-national data analysis. Examples will be given and replicated through R programmes.
The course is designed to exploit the interactive capabilities of online technology, combining annotated readings, short pre-recorded lectures, and live group work. It combines pre-class activities and live/online interaction. You will be given annotated and interactive readings which we will discuss ahead of the course. You should have completed the readings and watched the pre-recorded lectures on the key topics. The pre-recorded lectures take two forms: a methodological presentation and an illustration, through a published text or a data analysis, explained in plain English. The main tables or graphics will serve as key elements to understand the substantive issues of the methods.
There will be two hours each day, of live, in-class teaching. During these two hours we will review the main methodological issues and concepts related to the pre-recorded presentations and annotated readings.
We will set up an online Slack community to discuss course-related matters. The instructor will provide R scripts for running analysis and you will develop and complete them as your project work. During office hours, you’ll also have the chance to sign up for a quick one-to-one consultation with the Instructor or TA.
The course will consist of five sessions, organised in three main topics
The substantial and main methodological issues of comparing countries through statistical techniques
How the reasonings of statistical models do this ‘country effects’ analysis, through classical techniques like linear regression models, logit and loglinear models. We will pay attention to the fundamental problem of comparing regression estimates from one country to another one, and the sometimes tricky issues of it.
How data reduction techniques are used, and can be used, in cross-national analysis, through classical techniques like PCA. We will pay attention to another fundamental problem of comparative analysis: can we use the same instruments (survey questionnaire items) across countries, and what does it mean to run scaling analysis across it? Friday’s session will provide some short but important extensions to multilevel analysis and structural equations models that will prepare you to attend other courses more specialised in these techniques.
You must be familiar with basic statistical inference and regression models. If you are not, take the course Introduction to Inferential Statistics before you sign up for this one.