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Prof Fiona Steele COL 7.12

This course is available on the MPhil/PhD in Health Policy and Health Economics and MPhil/PhD in Statistics. This course is available as an outside option to students on other programmes where regulations permit.

A knowledge of probability and basic statistical theory, including linear regression and logistic regression.

Please log into moodle.lse.ac.uk and self-enrol in the 'R for Statistics Pre-sessional

A practical introduction to methods for the analysis of repeated measures data, including continuous and binary outcomes. Topics include: longitudinal study designs, models for two measurements, (random effects) growth curve models, marginal models, missing data, latent class models, models for binary data and dynamic (autoregressive) models. The course will have an applied emphasis with fortnightly computer classes using R.

This course will be delivered through a combination of lectures and computer classes totalling a minimum of 30 hours in WT.

Students are required to install R on their own laptops for use in the computer workshops.

This course includes a reading week in Week 6 of WT.

Students will be expected to produce 4 exercises in the WT.

Coursework assigned fortnightly and returned to students via Moodle with feedback.

• Hedeker D, Gibbons RD. Longitudinal Data Analysis. Hoboken, New Jersey: John Wiley & Sons, Inc. (2006).
• Rabe-Hesketh S,  Skrondal A. (2012) Multilevel and Longitudinal Modeling Using Stata, Third Edition. Volume I: Continuous Responses. College Station, Texas: Stata Press.
• Singer JD, Willett JB. Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. New York: Oxford University Press (2003). (Part I only).

Coursework (100%, 4000 words) in the ST.

Assessment is by 100% coursework which is given to students in week 8