Abstract:

This article will cover concepts of association and outcomes, introduce standard epidemiological concepts of incidence and prevalence, define and describe relative risk, absolute risk, attributable risk and the various methods for calculating those quantities in different observational research designs. Definitions of and methods for reducing bias are major components of this section.

Epidemiology is the study of disease in populations. It thus differs from the more conventional medical approaches to the study of disease that is normally concerned with the study of disease processes in affected individuals.Cohort, cross sectional, and case-control studies are collectively referred to as observational studies. Often these studies are the only practicable method of studying various problems, Cohort studies are used to study incidence, causes, and prognosis. Because they measure events in chronological order they can be used to distinguish between cause and effect. Cross sectional studies are used to determine prevalence. They are relatively quick and easy but do not permit distinction between cause and effect. Case controlled studies compare groups retrospectively. They seek to identify possible predictors of outcome and are useful for studying rare diseases or outcomes.

The crucial point of a clinical trial is the aim of investigating the difference of the patient groups caused only by the treatment procedures that are applied. If other kinds of differences exist (such as systematic differences) between the groups to be formed, then the outcomes are supposed to be biased. Forms of bias can corrupt a study at any phase, including patient selection (selection and membership bias), study performance (performance and information bias), patient follow-up (non responder and transfer bias), and outcome determination (detection, recall, acceptability, and interviewer bias).

The two common methods that are used to reduce the bias are randomization and blinding. The aim of randomization in clinical trials is the creation of groups that are comparable for any known or unknown, potentially confounding variables. Randomization, if done properly, ensures strengthening both the internal validity by minimizing selection bias and external validity by providing a correct basis for generalization. Simple randomization, weighted randomization, block randomization, stratified randomization, and minimization methods are discussed in this article.

Keywords: Epidemiology, simple randomization, block randomization, stratified randomization, minimization and blinding.

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