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Population Health: Study Design

Health care professionals increasingly have to make clinical decisions in aging and diverse populations.
Course from Coursera
 997 students enrolled
 en
You will be able to formulate a good research question
You will be able to interpret and apply different frequency and effect measures
You will be able to recognize errors and deal with bias and confounding
You will be able to describe basic principles of causal inference

Health care professionals increasingly have to make clinical decisions in aging and diverse populations. Also, they have to deal with rising health care costs, fragmented health care supply and advancing medical technologies and IT systems. These developments go beyond every day practice and will require new skills. In this course we will walk you through key steps in designing a research study, from formulating the research question to common pitfalls you might encounter when interpreting your results. We will focus primarily on analytical studies used in etiological research, which aims to investigate the causal relationship between putative risk factors (or determinants) and a given disease or other outcome. However, the principles we will discuss hold true for most research questions, and you will also encounter these study designs in prognostic and diagnostic research settings.

Population Health: Study Design
Free
per course
Incentives
100% online
Flexible deadlines
Intermediate Level
Approx. 28 hours to complete
English
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