Introduction
Welcome
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What you should know
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Using the exercise files
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1. Epidemiology and Causal Inference
Definition of epidemiology
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Terms about data
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Definition of exposure and outcome
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Populations vs. samples
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Scientific method in epidemiology
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Bradford Hill criteria: Part one
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Bradford Hill criteria: Part two
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2. Study Designs
Overview of human research
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Observational study vs. experiment
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Descriptive vs. analytic study designs
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Cross-sectional study design
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Case-control study design
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Levels of evidence
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3. Measures of Association
Introduction to the 2x2 table
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Prevalence ratio
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Odds ratio in a cross-sectional study
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Odds Ratio in a case-control study
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Conclusion about the 2x2 table
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4. Planning a Study
Definition of confounders
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Using a web of causation to identify confounders
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Tools for reviewing the scientific literature
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Reviewing existing scientific literature
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Establishing a working hypothesis
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Choosing a dataset
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Final dataset considerations
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5. Planning the Analytic Dataset
Definition of data curation
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Requirements for a cross-sectional or case-control analytic dataset
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Setting up a data dictionary
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Operationalizing the subpopulation
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Operationalizing the exposure, outcome, and confounders
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Documenting transformed variables in the data dictionary
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Conclusion
Review of the course
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Preparation for part two
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Ex_Files_Designing_Big_Data_Healthcare_Pt_1.zip
(1.0 MB)
Glossary_Designing_Big_Data_Healthcare_Studies_Part1.zip
(1000 KB)