Designing your Research Project. Ivan J Perry Department of Epidemiology & Public Health University College Cor. Learning objectives. Understand the nature of science, with particular reference to the core concept of measurement of causes and effects
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Ivan J Perry
Department of Epidemiology & Public Health
University College Cor
It is suggested that occupational exposure to volatile anaesthetic agents causes depression. You wish to test this hypothesis.
Seeking to understand the world by a process of observation or experimentation
Measurement - core activity
Measurement of causes and effects or exposures (gene and environment) and disease
To test hypothesis relating cause to effect
Hypothesis must be testable/capable of being disproved or refuted
In the late eighteenth century, Antoine Lavoisier, introduced the scientific approach to problem solving:
Observations or Experiment
Quantitative Research Project
Question or hypothesis:must be clearly stated (descriptive vs.. analytical research) Would qualitative methods be more appropriate?
Science/research:essentially an exercise in measurement
Study design:appropriate to question/hypothesis and feasible?
Be as specific as possible (e.g. Prevalence or Incidence)
Prevalence of Asthma in children with and without pets at home.
Incidence of Diabetes in smokers and non-smokers
For Quantitative Work
Randomised Controlled Trial
Quantitative Study Designs
How will exposure and outcomes be measured?
How will validity (accuracy) and reliability (precision) be determined?
Are established questionnaires/instruments available?
Need for standardised methods to minimise random error (chance) and systematic measurement error (measurement bias).
Define target population:-to whom will the findings apply
Study Population:-available for study -sufficiently representative of target population
Study Sample:-representative (in statistical sampling terms) of study population
Concept of sampling:-variation/sampling error
Study population and study sample?
Methods of sampling: random, stratified, systematic, cluster, convenience.
Representativeness of sample (selection bias).
Methods of recruitment and expected response rate (selection bias)
Sample size (chance, type I and type II errors).
Data collection methods, questionnaires (interview or postal), physical measurements, blood tests.
Data to be collected (potential confounding variables).
Avoid Microsoft Excel
Conflicts of Interests