ST332 Medical Statistics

ST332-15 Medical Statistics

Academic year: 22/23
Department: Statistics
Level: Undergraduate Level 3
Module leader: Keith Abrams
Credit value: 15
Module duration: 10 weeks
Assessment: Multiple
Study location: University of Warwick main campus, Coventry

Introductory description

This module runs in Term 2 and is available for students on a course where it is a listed option and as an Unusual Option to students who have completed the prerequisite modules.

Pre-requisite: ST346 Generalised linear models for Regression and Classification

Results from this module can be partly used to determine exemption eligibility in the Institute and Faculty of Actuaries (IFoA) modules CS1.

Module web page

Module aims

Modern applications of statistics to medicine are highly developed, and many medical research papers employ statistical techniques. Large numbers of statisticians are employed in medical research establishments, particularly in pharmaceutical companies and medical schools. Medical statistics continues to be a buoyant area for statistical recruitment. The course will explain why and how statistics is used in medicine, and study some of the statistical methods commonly used in medical research. We will include examples from our own research. The statistical techniques applied to medical data are also relevant in other applications.

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

Study designs: cohort, case-control and survey designs; randomised clinical trials; adaptive clinical trial designs.
Analysis of censored survival data: Life tables; hazard and survival functions; Kaplan-Meier survival curves; parametric survival models, the proportional hazards regression model.
Systematic reviews and meta-analysis: Systematic reviews summarise evidence on particular medical topics; meta-analyses use statistical methods such as glms to summarise studies included in systematic reviews; publication bias and funnel plots; Cochrane reviews.

Learning outcomes

By the end of the module, students should be able to:

appreciate the role of statistics in medical research
understand some of the statistical principles of good practice in medical investigations
understand how to use and interpret generalised linear models and survival analysis in medical data analysis

Indicative reading list

The books listed are suggestions. Some provide general background [1, 2, 3, 5, 11, 12, 16]; others are more focussed on statistical methodology [4, 6, 7, 8, 9, 10, 13, 14, 15]. In many cases, there will be other editions, which you can easily find through the library. I requested multiple copies of the most popular books; the essential material is in the older as well as newer editions. In addition, some e-books are now available through the library.

[1] D.G. Altman. Practical Statistics for Medical Research. Chapman and Hall, London, 1991.
[2] P Armitage and G Berry. Statistical Methods in Medical Research. Blackwell, Oxford, 2 edition, 1987.
[3] M Bland. An introduction to medical statistics. Oxford University Press, Oxford, 2 edition, 1995.
[4] M Borenstein. Introduction to meta-analysis. John Wiley & Sons, Chichester, U.K., 2009.
[5] M J Campbell and D Machin. Medical statistics: a commonsense approach. Wiley, Chicester, 3 edition, 1999.
[6] D. Collett. Modelling binary data. Chapman & Hall, London, 1991. 0412387905.
[7] D. Collett. Modelling survival data in medical research. Chapman & Hall, London, 3 edition, 2014.
[8] D R Cox and D Oakes. Analysis of Survival Data. Chapman & Hall, London, 1984.
[9] D R Cox and E J Snell. Analysis of Binary data. Chapman & Hall, London, 2 edition, 1989.
[10] AJ Dobson and AG Barnett. An introduction to generalized linear models. CRC Press, Boca Raton, 2008. 3rd ed.
[11] JV Freeman, SJ Walters, and MJ Campbell. How to display data. Blackwell (BMJ books), Oxford, 2008.
[12] S M Gore and D G Altman. Statistics in Practice. British Medical Association, London, 1982.
[13] M.K.B Parmar and D Machin. Survival analysis: a practical approach. Wiley, Chichester, 1995. 0471936405.
14] G Schwarzer, JR Carpenter, and G Rücker. Meta-analysis with R. Springer, Cham, 2015.
[15] AJ Sutton, KR Abrams, DR Jones, RA Sheldon, and F Sung. Methods for meta-analysis in medical research. Wiley, Chichester, 2000.
[16] E R Tufte. The Visual display of quantitative information. Graphics Press, Cheshire,
1983.

View reading list on Talis Aspire

Research element

Sourcing and summarizing medical research articles.
Novel secondary analysis of data.
Defining research questions and evaluating appropriate study designs.

Interdisciplinary

Students are required to study medical research articles, learn some medical terms, and translate the results of statistical analyses into summaries suitable for medical professionals and for the general public.

International

Students will be expected to review medical articles published by non-UK research groups.

Subject specific skills

-To understand the relevance of generalized linear models in analysis of medical data, and good practice in fitting and interpreting such models.
-To understand the analysis of survival data from medical studies, and good practice in fitting and interpreting such models.
-To appreciate the particular study the role of statistics in the design.

Transferable skills

Appreciation of the role of statistics in the design and analysis of studies addressing questions related to health and other aspects of society.
Competence in using descriptive statistics, generalized linear models and survival analysis to investigate and summarise data.

Study time

Type	Required	Optional
Lectures	30 sessions of 1 hour (25%)	2 sessions of 1 hour
Practical classes	5 sessions of 1 hour (4%)
Private study	85 hours (71%)
Total	120 hours

Private study description

Weekly revision of lecture notes and materials, wider reading, practice exercises.

Costs

No further costs have been identified for this module.

You do not need to pass all assessment components to pass the module.

Students can register for this module without taking any assessment.

Assessment group D3

	Weighting	Study time	Eligible for self-certification
Group Project	10%	15 hours	No
Due in Term 2 Week 6. You will work in a group to use specified data sets to address questions related to ordinary linear regression, carry out analysis and then present, discuss and evaluate the results. In addition to the word limit, you may include up to three figures and three tables. You must give a word count. Your ST332 Group Project must include a statement of the contributions of each group member; this is not included in the word count.
Individual Project	10%	15 hours	Yes (extension)
Due in Term 2 Week 10. You will work on specified data sets and research articles to address questions related to generalised linear regression, carry out analysis and then present, discuss and evaluate the results. In addition to the word limit, you may include up to three figures and three tables. You must give a word count.
In-person Examination	80%		No
The examination paper will contain four questions, of which the best marks of THREE questions will be used to calculate your grade. Answerbook Pink (12 page) Students may use a calculator Cambridge Statistical Tables (blue)

Assessment group R1

	Weighting	Study time	Eligible for self-certification
In-person Examination - Resit	100%		No
The examination paper will contain four questions, of which the best marks of THREE questions will be used to calculate your grade. ~Platforms - Moodle

Feedback on assessment

Marked assignments will be available for viewing at the support office within 20 working days of the submission deadline. Cohort level feedback and solutions will be provided, and students will be given the opportunity to receive feedback via face-to-face meetings.

Solutions and cohort level feedback will be provided for the examination.

Past exam papers for ST332

Pre-requisites

Either ST218 and ST219 or ST220. Menu does not allow this.
ST346 is strongly recommended.

Courses

This module is Optional for:

Year 3 of UCSA-G4G1 Undergraduate Discrete Mathematics
Year 3 of UCSA-G4G3 Undergraduate Discrete Mathematics
Year 4 of UCSA-G4G4 Undergraduate Discrete Mathematics (with Intercalated Year)
Year 4 of UCSA-G4G2 Undergraduate Discrete Mathematics with Intercalated Year
USTA-G300 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics
- Year 3 of G300 Mathematics, Operational Research, Statistics and Economics
- Year 4 of G300 Mathematics, Operational Research, Statistics and Economics

This module is Option list A for:

USTA-G1G3 Undergraduate Mathematics and Statistics (BSc MMathStat)
- Year 3 of G1G3 Mathematics and Statistics (BSc MMathStat)
- Year 4 of G1G3 Mathematics and Statistics (BSc MMathStat)
USTA-G1G4 Undergraduate Mathematics and Statistics (BSc MMathStat) (with Intercalated Year)
- Year 4 of G1G4 Mathematics and Statistics (BSc MMathStat) (with Intercalated Year)
- Year 5 of G1G4 Mathematics and Statistics (BSc MMathStat) (with Intercalated Year)
Year 3 of USTA-GG14 Undergraduate Mathematics and Statistics (BSc)
Year 4 of USTA-GG17 Undergraduate Mathematics and Statistics (with Intercalated Year)
Year 3 of USTA-Y602 Undergraduate Mathematics,Operational Research,Statistics and Economics
Year 4 of USTA-Y603 Undergraduate Mathematics,Operational Research,Statistics,Economics (with Intercalated Year)

This module is Option list B for:

UMAA-G105 Undergraduate Master of Mathematics (with Intercalated Year)
- Year 4 of G105 Mathematics (MMath) with Intercalated Year
- Year 5 of G105 Mathematics (MMath) with Intercalated Year
Year 3 of UMAA-G100 Undergraduate Mathematics (BSc)
UMAA-G103 Undergraduate Mathematics (MMath)
- Year 3 of G100 Mathematics
- Year 3 of G103 Mathematics (MMath)
- Year 4 of G103 Mathematics (MMath)
UMAA-G106 Undergraduate Mathematics (MMath) with Study in Europe
- Year 3 of G106 Mathematics (MMath) with Study in Europe
- Year 4 of G106 Mathematics (MMath) with Study in Europe
Year 4 of UMAA-G101 Undergraduate Mathematics with Intercalated Year

This module is Option list C for:

Year 3 of USTA-G302 Undergraduate Data Science
Year 3 of USTA-G304 Undergraduate Data Science (MSci)
Year 4 of USTA-G303 Undergraduate Data Science (with Intercalated Year)

This module is Option list D for:

Year 4 of USTA-G300 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics
Year 5 of USTA-G301 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics (with Intercalated

This module is Option list E for:

Year 4 of USTA-G300 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics
Year 5 of USTA-G301 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics (with Intercalated

This module is Option list F for:

Year 3 of USTA-G300 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics
USTA-G301 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics (with Intercalated
- Year 3 of G30H Master of Maths, Op.Res, Stats & Economics (Statistics with Mathematics Stream)
- Year 4 of G30H Master of Maths, Op.Res, Stats & Economics (Statistics with Mathematics Stream)

Catalogue

Resources

Feedback and Evaluation

Grade Distribution

Timetable

Assessments dates for Statistics modules, including coursework and examinations, can be found in the Statistics Assessment Handbook.