Multivariate Statistical Techniques for Comparing Countries

Key topics covered

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’:

• Tuesday and Wednesday ꟷ statistical modelling techniques such as linear regression, logit and loglinear models
• Thursday and Friday ꟷ data reduction techniques such as principal components and scaling techniques. 

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.

How the course will work online

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 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 will be two hours each day of live, in-class teaching. During this time we will review the main methodological issues and concepts related to the pre-recorded presentations and annotated readings.

We will discuss course-related matters in an online Slack community. 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.

The course will consist of five sessions, organised in three main topics

Topic 1

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?

Topic 2

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. 

Topic 3

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.