Lugano, Switzerland

Multilevel Modelling

when 22 August 2022 - 26 August 2022
language English
duration 1 week
fee CHF 700

Populations commonly exhibit complex structure with many levels, so that patients (level 1) are assigned to clinics (level 2); while individuals (1) may ‘learn’ their behaviour in the context of households (2) and neighbourhood cultures (3). In many cases, the survey design reflects the population structure, so in a survey of voting intentions respondents (1) are clustered by constituencies (2), or in a study of school attainment, pupils (1) are clustered in schools (2). Multilevel models are currently being applied to a growing number of social science research areas, including educational and organisational research, epidemiology, voting behaviour, sociology, and geography. Data at different levels are often seen as a convenience in the design which is a nuisance in the analysis. However, by using multilevel models we can model simultaneously at several levels, gaining the potential for improved estimation, valid inference, and a better substantive understanding of the realities of social organisation.

In this course, and building on standard single-level models, we develop the two-level model with continuous predictors and response. Examples include house-prices varying over districts, and pupil progress varying by school. These models will then be extended to cover complex variation, both within and between levels, three-level models, and models with categorical predictors and response (the multilevel logit model). We end with a consideration of estimators including maximum likelihood and Bayesian MCMC estimators. Throughout the course, we shall use graphical examples, verbal equations, algebraic formulation, class-based model interpretation, and practical exercises that will be completed using R.

Course prerequisites:

Participants should be familiar with regression modelling and inferential statistics, especially regression intercepts and slopes, standard errors, residuals, and the concepts of variance and co-variance. Even so, the aim is not to cover mathematical derivations and statistical theory, but to provide a conceptual framework and ‘hands-on’ experience. It does not require prior knowledge of multilevel modelling. In terms of software, a moderate level of experience using R is required.

Course leader

Andrew Bell: Director of Research and Lecturer in Quantitative Social Sciences, University of Sheffield

Target group

Everyone who is interested; there are no formal requirement. Note that many workshops have some prerequisites.

The Summer School workshops are conceived for those who need to deepen and widen their methodological knowledge and skills for their work, research projects and (PhD) theses: students, junior and senior researchers, practitioners from academia and outside academia at any stage of their careers whenever the need for further training in methodology arises.

Course aim

In this course, and building on standard single-level models, we develop the two-level model with continuous predictors and response. Examples include house-prices varying over districts, and pupil progress varying by school. These models will then be extended to cover complex variation, both within and between levels, three-level models, and models with categorical predictors and response (the multilevel logit model). We end with a consideration of estimators including maximum likelihood and Bayesian MCMC estimators. Throughout the course, we shall use graphical examples, verbal equations, algebraic formulation, class-based model interpretation, and practical exercises that will be completed using R.

Credits info

The Summer School cannot grant credits. We only deliver a Certificate of attendance, i.e. we certify your
presence

If you consider using Summer School workshops to obtain credits (ECTS), you will have to investigate at your home institution (contact the person/institute responsible for your degree) to find out whether they recognize the Summer School, how many credits can be earned from a workshop/course with roughly 35 hours of teaching, no graded work, and no exams.

Make sure to investigate this matter before registering, if this is important to you.

Fee info

CHF 700: Reduced fee: 700 Swiss Francs per weekly workshop for students (requires proof of student status).

These fees includes also participation in one of the preliminary workshops (two-day workshop preceding the Summer School).
To qualify for the reduced fee, you are required to send a copy of an official document that certifies your current student status or a letter from your supervisor stating your actual position as a doctoral or postdoctoral student. Send this letter/document by e-mail to methodssummerschool@usi.ch.
CHF 1100: Normal fee: 1100 Swiss Francs per weekly workshop for all others.
These fees includes also participation in one of the preliminary workshops (two-day workshop preceding the Summer School).

Scholarships

As the Summer School is financed through participant’s fees alone and has no funds of its own, it cannot offer any scholarship, grants or financial aid.