Learn how to enter native and calculated variables into the data dictionary.
- [Narrator] In the last lecture,…we began the data dictionary…and added a native variable, veteran status.…Here, we will add three more native variables:…alcohol consumption, sleep duration, and asthma status.…Again, we return to the code book.…Let's find the alcohol variable we want to use.…I'm going to use Control + F and look for alcohol.…Here we are, ALCDAY5.…This is a pretty complicated variable, so let's document it.…Let's go over to the data dictionary,…where I already did that.…
The question is simple enough.…During the past 30 days, how many days per week or per month…did you have at least one drink of any alcoholic beverage,…such as beer, wine, a malt beverage, or liquor?…But let's look at the coding I documented on the tab.…See how complex the coding of this field is?…One in the first position means per week.…The other two positions are how many times per week.…But note that two in the first position…means "in the past 30 days."…The other positions are how many times in the past 30 days.…
And then there are these other codes.…
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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