ÐÓ°ÉÂÛ̳

 

Not available in 2020/21
ST442      Half Unit
Longitudinal Data Analysis

This information is for the 2020/21 session.

Teacher responsible

Prof Fiona Steele COL 7.12

Availability

This course is available on the MSc in Social Research Methods, MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (ÐÓ°ÉÂÛ̳ and Fudan), MSc in Statistics (Financial Statistics) (Research), MSc in Statistics (Research), MSc in Statistics (Social Statistics) and MSc in Statistics (Social Statistics) (Research). This course is available as an outside option to students on other programmes where regulations permit.

Pre-requisites

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

Course content

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 and dynamic (autoregressive) models. The course will have an applied emphasis with fortnightly computer classes using the Stata software.

Teaching

20 hours of lectures and 10 hours of computer workshops in the LT.

Week 6 will be used as a reading week.

Formative coursework

Coursework assigned fortnightly and returned to students with comments/feedback during the computer sessions.

Indicative reading

Singer JD, Willett JB. (2003) Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. New York: Oxford University Press. (Part I only).

Rabe-Hesketh S,  Skrondal A. (2012) Multilevel and Longitudinal Modeling Using Stata, Third Edition. Volume I: Continuous Responses. College Station, Texas: Stata Press.

Hedeker D, Gibbons RD. (2006) Longitudinal Data Analysis. Hoboken, New Jersey: John Wiley & Sons, Inc.

Assessment

Exam (100%, duration: 2 hours) in the summer exam period.

Important information in response to COVID-19

Please note that during 2020/21 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the situation of students in attendance on campus and those studying online during the early part of the academic year. For assessment, this may involve changes to mode of delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.

Key facts

Department: Statistics

Total students 2019/20: 25

Average class size 2019/20: 25

Controlled access 2019/20: Yes

Value: Half Unit

Personal development skills

  • Problem solving
  • Application of numeracy skills