### Module Details

 The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
 Title MEDICAL STATISTICS Code MATH364 Coordinator Dr S Lane Health Data Science Slane@liverpool.ac.uk Year CATS Level Semester CATS Value Session 2021-22 Level 6 FHEQ Second Semester 15

### Aims

The aims of this module are to: demonstrate the purpose of medical statistics and the role it plays in the control of disease and promotion of health explore different epidemiological concepts and study designs apply statistical methods learnt in other programmes, and some new concepts, to medical problems and practical epidemiological research enable further study of the theory of medical statistics by using this module as a base.

### Learning Outcomes

(LO1) identify the types of problems encountered in medical statistics

(LO3) apply appropriate statistical methods to problems arising in epidemiology and interpret results

(LO4) explain and apply statistical techniques used in survival analysis

(LO5) critically evaluate statistical issues in the design and analysis of clinical trials

(LO6) discuss statistical issues related to systematic review and apply appropriate methods of meta-analysis

(LO7) apply Bayesian methods to simple medical problems.

(S1) Problem solving skills

### Syllabus

Medical Statistics: definitions and examples. Introduction : Motivating application to epidemiology. Epidemiology : routine data, standardisation of illness rates, surveys, screening, cohort studies, case-control studies, causality, multiple linear and logistic regression. Examples: Down‟s syndrome and congenital heart disease, prevalence of diabetes, the relationship between muscle strength and lean body mass, cigarette smoking and risk of lung cancer Survival analysis : parametric and semi-parametric survival functions, Kaplan-Meier survival curve, log-rank test, Cox proportional hazards regression analysis. Example: IUD usage, survival times of patients with tongue cancer and the role of different tumour types Clinical trials : parallel two group design, randomisation, blinding, sample size, analysis, cross-over trials. Examples: Effectiveness of anti-depressants, Vit. D supplement for htpocalcaemia Systematic reviews and meta-analysis : introduction to systematic review, publication bias, funnel plot, test for heterogeneity. Example: comparison of aspirin against placebo for preventing death following myocardial infarction. Bayesian methods : introduction to Bayesian analysis in clinical trials. Example: comparison of neutron and photon therapy for pelvic cancer.

### Assessment

EXAM Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
Final Assessment open book and remote Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :Second  1 hour time on task    50
CONTINUOUS Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
Homework 3  equivalent to 2-5 si    10
Homework 2  equivalent to 2-5 si    10
Homework1  equivalent to 2-5 si    10
Class Test 1  around 60-90 minutes    20