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Introduction to Epidemiology and Biostatistics for Clinicians

Course Information

Duration: 1 hour per week for 6 weeks

When: Thursdays, April 21th, 28th, May 5th, 12th, 19th, 26th

Time: 17:00-18:00

Potential Participants: This course is targeted to clinicians (physicians, nurses, other health care providers) interested in learning about the basics of epidemiological research with a focus on applications in clinical care. This course may be of interest for those wishing to understand epidemiological terminology, basic statistical testing often used in the clinical setting, and a better appreciation of the scientific literature in medical research.

Description: This course will use a pragmatic approach to introduce research design, analysis, and interpretation of clinical data. Epidemiologic terminology and basic biostatistical methods will be explained and used in context. In addition to general concepts such as types of data and study designs, it will cover simple statistical methods that are useful in secondary data analysis. We will use examples from the literature including publications from The Irish Longitudinal Study on Ageing (TILDA) to put data concepts into context.

Prerequisites: None (training as a health care clinician recommended).

Materials: NOT REQUIRED but may be helpful to seminar participants: Hulley, Cummings, et al. Designing Clinical Research (3rd edition). Lippencott, Williams & Wilkins (publishers). 2013. Price = €76.

Questions: Please contact Prof. Fitzpatrick at fitzpa13@tcd.ie

Course Content

Class 1: INTRODUCTION

  1. Course Overview
  2. Components of a Research Study
  3. Epidemiology Terminology
  4. The Irish Longitudinal Study on Ageing

Class 2: THE RESEARCH QUESTION

  1. Types of Data
  2. How Data are used in Research Questions
  3. Developing a Research Question
  4. Hypothesis Testing
  5. Statistical Inference
  6. Safety and Ethics

Class 3: STUDY DESIGN

  1. Cross-sectional Studies
  2. Case-Control Studies
  3. Observational Cohorts
  4. Randomized Controlled Trials (RCTS)
  5. Sampling
  6. Examples

Class 4: DESCRIPTIVE STATISTICS

  1. Frequencies
  2. Measures of Central Tendancies
  3. Associations
  4. Examples

Class 5: LINEAR REGRESSION

  1. Concept
  2. Parameters and Interpretation
  3. Examples

Class 6: LOGISTIC REGRESSION

  1. Concept
  2. Parameters and Interpretation
  3. Examples