Modelling Structured Data

Aims:
? to give students the ability to recognise and appreciate the issues associated with analysing repeated measurement data
? to describe a range of statistical methods, both traditional and modern, for the analysis of repeated measurement data
? to train students to identify and apply appropriate techniques, using statistical software, and to interpret the results.
Assessable learning outcomes:
By the end of the module it is expected that the student will have:
? an awareness of repeated measurements and methods for analysing data in this form
? the ability to compare and contrast different approaches for analysing repeated measurements
? the ability to perform common types of analysis and interpret the results.

Additional outcomes:

Outline content:
Synopsis
Many statistical techniques are only applicable when observations are independent. When successive observations on quantities, such as weight or a measure of lung function, are made the repeated measurements will usually be correlated. Traditional statistical methods used in the analysis of this form of data will be described, such as the summary statistics approach, split-plot analysis of variance and repeated measures multivariate analysis of variance. More modern approaches utilise mixed models, which have become popular for analysing repeated measurement data. Such models will be considered in detail.

Syllabus
Summary statistics
Split-plot analysis of variance
Repeated measures multivariate analysis of variance
Mixed models - marginal and random coefficient models
Maximum likelihood and REML fitting methodologies
Use of SAS PROC GLM and PROC MIXED.
Brief description of teaching and learning methods:
Lectures supported by problem sheets and practicals.

Summative Assessment Methods:
Written exam 70%
Set exercise 30%

Other information on summative assessment:
One assignment and one examination.

Formative assessment methods:
Problem sheets and computer-based practicals.

Penalties for late submission:
Penalties for late submission on this module are in accordance with the University policy.
The following penalties will be applied to coursework which is submitted after the deadline for submission:

where the piece of work is submitted up to one calendar week after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for the piece of work will be deducted from the mark;
where the piece of work is submitted more than one calendar week after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

You are strongly advised to ensure that coursework is submitted by the relevant deadine. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.
(Please refer to the Undergraduate Guide to Assessment for further information: http://www.reading.ac.uk/internal/exams/student/exa-guideUG.aspx)

Length of examination:
2 hours.

Requirements for a pass:
A mark of 40% overall.