Learn how to use the documented exclusion frequencies in the data reduction spreadsheet to make a data reduction diagram.
- [Instructor] In this section, you will have to use…diagramming software.…Like I said before, I use online software called…Gliffy.com, and I'll show you how that turned out for me,…then, referring to our data reduction spreadsheet,…we'll walk through the diagram together.…There are a few reasons why you should make…a data reduction diagram.…Often these are included in publications.…First, it helps you be clear to your readers about how…you defined your subpopulation, that's the subject…of your study.…
Next, it allows the audience to evaluate selection bias.…Image that almost all of the alcohol drinking variables…were invalid, and that the ones that were filled in,…said the respondents drank very little alcohol.…That would suggest selection bias, or that people who…drank a lot didn't report it, and so they selected…themselves out of our criteria in a biased way.…Finally, having a clear diagram allows others to replicate…defining your exact subpopulation in their future studies,…if they want to build on your work.…
This detailed, practical course is designed to help those in the field of public health, medicine, and data science to edit, analyze, and interpret data. Learn how to code new variables, use the forward-stepwise modeling process, and document your decisions. Find out how to visualize results by generating charts and graphics, and how to add tables and figures to your documentation. This course helps equip you to independently design, develop, and execute a full BRFSS analysis, and even publish your results in scientific publications or journals.
- Reviewing survey data and documentation
- Conducting a BRFSS analysis
- Understanding naming conventions
- Editing variables
- Reviewing distributions
- Generating an analytic dataset
- Developing descriptive statistics to answer prespecified hypotheses
- Preparing publication-worthy tables and plots
Skill Level Advanced
1. What Is the BRFSS?
2. Designing Your Metadata
3. Reading in Data and Applying Exclusions
4. Preparing for Descriptive Analysis
5. Conducting Descriptive Analysis
Making a frequency macro4m 8s
6. Descriptive Analysis: Weights and Tests
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