With guidance from the data dictionary, learn how to use an R list to trim off unneeded native variables from the analytic data set.
- [Instructor] This lecture is about…keeping the native variables we need…after reading in the data set.…So let me remind you where we've gone…up to now in this chapter.…First, I talked about what packages there were,…and we loaded the foreign package together.…Then we made some code using the foreign package,…and downloaded the BRFSS data set,…in the .xpt format, and read it in.…After that, I explained to you…about naming conventions for data set and code.…Now, in this movie, we'll go back to the code we made…to read in the data set,…and we'll save it according to our naming conventions.…
And, we will use our data dictionary as a guide…to just keep the native variables we need…from the large BRFSS data set.…We made some code to call up the foreign library,…and read in the data.…Okay, now that we learned about naming conventions…in section three, let's name this code.…I like to name my code starting with three integers…so it sorts in order of how you run it, like I said.…I like my editing data code to start with one,…
Author
Released
12/12/2016This 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
Duration
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Code Clinic: R (2015)
with Mark Niemann-Ross3h 24m Intermediate
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Introduction
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Welcome46s
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Introduction to the course1m 22s
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1. What Is the BRFSS?
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US risk factors5m 30s
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Introduction to the BRFSS2m 46s
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More on the BRFSS1m 50s
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Ethical use of BRFSS data4m 38s
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BRFSS resources2m 25s
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Installing R1m 50s
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Navigating in R2m 37s
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2. Designing Your Metadata
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Uses of a data dictionary4m 35s
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Understanding confounders4m 24s
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Making a web of causation6m 28s
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3. Reading in Data and Applying Exclusions
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Reading in BRFSS XPT data6m 57s
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Naming conventions5m 38s
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Keeping native variables5m 15s
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Operations in code3m 52s
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Generating exposure4m 43s
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Generating outcome variables3m 32s
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4. Preparing for Descriptive Analysis
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Generating the age variables4m 18s
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What is Table 1?4m 26s
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5. Conducting Descriptive Analysis
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Making a frequency macro4m 8s
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6. Descriptive Analysis: Weights and Tests
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Conclusion
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Review of the metadata6m 11s
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Uses of metadata5m 26s
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Review of the process3m 39s
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Video: Keeping native variables