ST332 Medical Statistics
Please note that all lectures for Statistics modules taught in the 2022-23 academic year will be delivered on campus, and that the information below relates only to the hybrid teaching methods utilised in 2021-22 as a response to Coronavirus. We will update the Additional Information (linked on the right side of this page) prior to the start of the 2022/23 academic year.
Throughout the 2021-22 academic year, we will be adapting the way we teach and assess your modules in line with government guidance on social distancing and other protective measures in response to Coronavirus. Teaching will vary between online and on-campus delivery through the year, and you should read the additional information linked on the right hand side of this page for details of how this will work for this module. The contact hours shown in the module information below are superseded by the additional information. You can find out more about the University’s overall response to Coronavirus at: https://warwick.ac.uk/coronavirus.
PLEASE NOTE: This module has expected changes coming in for 20/21 and the information shown below may not be accurate. Please see additional information for details.
All dates for assessments for Statistics modules, including coursework and examinations, can be found in the Statistics Assessment Handbook at http://go.warwick.ac.uk/STassessmenthandbook
ST332-15 Medical Statistics
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 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 (20%) | 2 sessions of 1 hour |
| Practical classes | 5 sessions of 1 hour (3%) | |
| Private study | 85 hours (57%) | |
| Assessment | 30 hours (20%) | |
| Total | 150 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. |
|||
| Individual Project | 10% | 15 hours | Yes (extension) |
|
Due in Term 2 Week 10. |
|||
| 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.
|
|||
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.
Pre-requisites
Either ST218 and ST219 or ST220. Menu does not allow this.
ST346 is strongly recommended.
To take this module, you must have passed:
Anti-requisite modules
If you take this module, you cannot also take:
- ST409-15 Medical Statistics with Advanced Topics
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-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:
- Year 3 of USTA-G304 Undergraduate Data Science (MSci)
- Year 4 of USTA-G303 Undergraduate Data Science (with Intercalated Year)
-
UMAA-G105 Undergraduate Master of Mathematics (with Intercalated Year)
- Year 3 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 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)