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.
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What you'll learn
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
Skills you'll gain
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There are 5 modules in this course
Welcome to Population Health: Study Design! In this module you will get to know what the scope is of this course and you will learn how to be successful at online studying.
What's included
2 videos3 readings1 discussion prompt1 plugin
In this module you will start to formulate a research question. You will be introduced to the most important study designs in epidemiology, and work out which study design fits your specific research question.
What's included
9 videos2 readings4 assignments4 discussion prompts1 plugin
In this module you will calculate frequency and effect measures, and apply them to your own research questions. In addition, you will practice with constructing a life table and drawing a Kaplan-Meier curve.
What's included
7 videos2 readings4 assignments1 discussion prompt1 plugin
In this module different types of error will be discussed, which can be either random or systematic in nature. Subsequently, you will learn to recognize bias and confounding. You will additionally gain hands-on experience with standardisation.
What's included
7 videos1 reading3 assignments2 discussion prompts1 plugin
In this module you will calculate with averages, learn basic principles of causal inference, and be introduced to the concepts of regression to the mean and intention to treat.
What's included
6 videos2 readings4 assignments2 discussion prompts2 plugins
Instructors
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Recommended if you're interested in Research
Johns Hopkins University
The University of Tokyo
University of Minnesota
University of Houston
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