## MATH2770 Medical Statistics

### 10 creditsClass Size: 200

Module manager: Dr L.V. Bogachev
Email: bogachev@maths.leeds.ac.uk

Taught: Semester 2 (Jan to Jun) View Timetable

Year running 2008/09

### Pre-requisites

 MATH1725 Introduction to Statistics

This module is approved as an Elective

### Module summary

New drugs and other treatments frequently appear on the market. However, before this stage, much research is carried out on a drug's effectiveness; this may often be measured in relation to other existing treatments. Issues involved include how to collect reliable data which is truly representative - without treating humans as guinea pigs. In medical trials (for example, heart transplant students) the success of the outcome may only be measurable some time later, so an analysis of the survival times can be carried out.

### Objectives

To provide an introduction to statistical methods of specific interest in medical applications.
On completion of this module, students should be able to:
(a) carry out appropriate nonparametric tests;
(b) describe various types of clinical trials;
(c) understand different sampling methods;
(d) carry out parametric and nonparametric survival analysis.

### Syllabus

New drugs and other treatments frequently appear on the market. However, before this stage, much research is carried out on a drug's effectiveness; this may often be measured in relation to other existing treatments. Issues involved include how to collect reliable data which is truly representative - without treating humans as guinea pigs. In medical trials (for example, heart transplant students) the success of the outcome may only be measurable some time later, so an analysis of the survival times can be carried out.

Topics covered include:
1. Design of medical studies. Double-blind randomized clinical trials; cross-over designs; cross-sectional, cohort and case-control studies; bias, confounding; observation studies.
2. Nonparametric tests. Mann-Whitney; Wilcoxon; Kolmogorov-Smirnov.
3. Epidemiology. Rates of disease; incidence and prevalence; risk and odds.
4. Survival analysis. Parametric models; Kaplan-Meier estimator.

### Teaching methods

Due to COVID-19, teaching and assessment activities are being kept under review - see module enrolment pages for information

 Delivery type Number Length hours Student hours Example Class 7 1.00 7.00 Lecture 22 1.00 22.00 Private study hours 71.00 Total Contact hours 29.00 Total hours (100hr per 10 credits) 100.00

### Methods of assessment

Due to COVID-19, teaching and assessment activities are being kept under review - see module enrolment pages for information

Coursework
 Assessment type Notes % of formal assessment In-course Assessment . 20.00 Total percentage (Assessment Coursework) 20.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Exams
 Exam type Exam duration % of formal assessment Standard exam (closed essays, MCQs etc) 2 hr 80.00 Total percentage (Assessment Exams) 80.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated