
This course is only available to social science PhD students who are studying at a UK university. The course is organised by the Centre for Multilevel Modelling for the South West Doctoral Training Centre (SWDTC), and subsidised by the LEMMA node of the National Centre for Research Methods. There are five places available for non-SWDTC students.
Studies using longitudinal data are generally concerned with either the change over time in a response variable (e.g. physical measures such as height and weight), or the timing of events (e.g. death or births). This course will introduce methods for addressing both types of question. Topics will include multilevel growth curve models and dynamic panel models for repeated measures on continuous outcomes, and continuous-time and discrete-time methods for event history data. The course will include practical sessions using Stata.
Prerequisites: Familiarity with multilevel modelling and logistic regression analysis to the level of knowledge obtained by completing Modules 5 and 6 of the Centre for Multilevel Modelling’s online course (http://www.bristol.ac.uk/cmm/learning/course-topics.html)
Instructor: Fiona Steele
Timings: On both days the course will start at 11am and finish at 5pm.
Course fee: The course is free of charge (but only open to social science PhD students registered at a UK university). Please note that no refreshments will be provided.
Registration: Please register your interest in attending the course by completing the online form at http://www.bris.ac.uk/cmm/software/support/workshops/bookings2.html. If you have any queries, email info-cmm@bristol.ac.uk. We will contact you by 30 April to let you know whether you have a place on the course.
Join our mailing list to receive news of any new workshops - please note that they quickly become fully-booked.
4-6 Jan-2012 - workshop now fully booked. We usually run this workshop annually in January but do not guarantee to do so every year.
Venue: Haggett Laboratory, School of Geographical Sciences,University of Bristol, University Road, Bristol BS8 1SS
Google map
This workshop provides an introduction to multilevel modelling. We assume that participants are familiar with single level regression models (to the level implied by Module 3 of our online multilevel modelling course) but have no prior knowledge of multilevel modelling. Theory sessions are accompanied by practical sessions using our software, MLwiN, in which participants get the chance to apply what they have learned to real datasets. No prior knowledge of MLwiN is assumed: the first practical takes participants right from the very basics. Throughout, there is an emphasis on how to interpret the models and on what kinds of research question they can be used to explore. For further information, see previous 'Introduction to multilevel modelling' workshop materials (the presentations will be similar but may be subject to minor changes)
2-4 April-2012 - workshop now fully-booked
Venue: Haggett Laboratory, School of Geographical Sciences,University of Bristol, University Road, Bristol BS8 1SS
Google map
This workshop will cover background theory and application of MCMC methods with a focus on multilevel modelling. We will in particular focus on model classes that benefit from MCMC estimation including discrete response models, cross classified models, multiple membership models and multivariate response models with missing data. Theory sessions are accompanied by practical sessions using our software, MLwiN, in which participants get the chance to apply what they have learned to real datasets. We will also showcase methods within MLwiN to speed up the MCMC estimation. Towards the end of the workshop we will describe the currently under-development STAT-JR software package and allow the participants the opportunity to use it and its interoperability features with other MCMC packages such as WinBUGS.
The workshop will start at 10.30am on the 2nd April and finish with lunch at 1pm on the 4th April.
Workshop FAQsNote: some of the documents on this page are in PDF format. In order to view a PDF you will need Adobe Acrobat Reader