9 February 2024
Multivariate Statistical Techniques for Comparing Countriesonline course
"Learn how different statistical methods treat the 'country effect', and how statistical models, scaling techniques and data reduction methods test for the 'invariance' of the relationship between variables across countries.
Need to know
This course requires an understanding of basic statistical inference and regression models. If you don't have this level of understanding, consider taking the Introduction to Inferential Statistics course before this one.
We begin with a review of the substantial and methodological problems the multivariate statistical analysis tries to solve in the comparison of countries, particularly what is a ‘country effect’ and how this translates in statistical terms.
On Monday, you will undertake activities that show very simple recalls using descriptive and bivariate techniques applied to ‘country effects’ problems.
Following this, you will work to understand the two main types of multivariate techniques, still applied to the same question of ‘country effects’:
• Tuesday / Wednesday ꟷ statistical modelling techniques such as linear regression, logit and loglinear models
• Thursday / Friday ꟷ data reduction techniques such as principal components and scaling techniques.
On 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 consists of five sessions, organised in three main topics, detailed below.
The substantial and main methodological issues of comparing countries through statistical techniques
• What does it mean to test for ‘country effects’; what are they?
• How does this translate into statistical terminology and methods?
• What are the main notions, concepts and vocabulary used in this research field?
How the reasonings of statistical models do this ‘country effects’ analysis, through classical techniques like linear regression models, logit, loglinear and multilevel models.
We will pay attention to the fundamental problem of comparing regression estimates from one country to another, and the sometimes tricky issues.
How data reduction techniques are used, and can be used, in cross-national analysis, through classical techniques like PCA.
We tackle 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 multi-level analysis and structural equations models, preparing you to attend other more specialised courses in these techniques.
How the course will work
The course will use interactive online technology, combining annotated readings, short pre-recorded lectures, and live group work. It combines pre-class activities and live interaction.
You should complete the readings and watch the pre-recorded lectures on key topics ahead of the course start date.
The 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 help you understand the substantive issues of the methods.
There are three hours of classroom teaching each day, during which you will review the main methodological issues and concepts related to the pre-recorded presentations and annotated readings. Following this, the TA will give one hour of practical examples.
In the afternoons, we will discuss course-related matters in an online Slack community (one hour of office hours). The Instructor will provide R scripts for running analysis and you will develop and complete them as a project. During office hours, you’ll also be able to sign up for a quick one-to-one consultation with the Instructor or TA."
Bruno Cautrès is attached to CEVIPOF – Centre de recherches politiques de Sciences Po (Paris), at the Fondation Nationale des Sciences Politiques in Paris.
The course is designed for a demanding audience (researchers, professional analysts, advanced students).
"This course offers an introduction to the main statistical techniques used to analyse cross-national comparative surveys data.
By the end, you will gain an understanding of 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.
During the course you will use R and/or Stata.
The course has two key points:
1.It offers a reasonable level of formalisation, as much as needed to understand the methods
2.It makes links between the different methods and the learning of complementarities between methods. "
"You can earn up to four credits for attending this course.
3 ECTS credits – Attend 100% of live sessions and engage fully with class activities.
4 ECTS credits – Attend 100% of live sessions, engage fully with class activities and complete a post-class assignment."
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