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Master Healthcare Analytics in R: BRFSS Data Science Pro

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4:13:11

  • 01 - Welcome.mp4
    00:46
  • 01 - U.S. risk factors.mp4
    05:30
  • 02 - Introduction to the BRFSS.mp4
    02:46
  • 03 - More on the BRFSS.mp4
    01:50
  • 04 - What is a descriptive BRFSS analysis.mp4
    04:57
  • 05 - Cross-sectional analysis in the BRFSS.mp4
    03:52
  • 06 - Ethical use of BRFSS data.mp4
    04:38
  • 07 - BRFSS resources.mp4
    02:25
  • 08 - Choosing R for a BRFSS analysis Some considerations.mp4
    03:51
  • 09 - Choosing R for a BRFSS analysis More considerations.mp4
    04:14
  • 10 - Installing R.mp4
    01:50
  • 11 - Navigating in R.mp4
    02:37
  • 12 - Installing the foreign package.mp4
    03:08
  • 13 - Installing necessary packages.mp4
    03:58
  • 01 - Uses of a data dictionary.mp4
    04:35
  • 02 - How to set up a data dictionary.mp4
    03:48
  • 03 - Adding to the data dictionary.mp4
    06:13
  • 04 - Understanding confounders.mp4
    04:24
  • 05 - Making a web of causation.mp4
    06:28
  • 06 - Designing confounders Age and smoking.mp4
    04:42
  • 07 - Designing confounders Other demographics.mp4
    04:19
  • 08 - Designing confounders Other variables used in analysis.mp4
    04:39
  • 01 - Reading in BRFSS XPT data.mp4
    06:57
  • 02 - Naming conventions.mp4
    05:38
  • 03 - Keeping native variables.mp4
    05:15
  • 04 - Applying the first exclusion.mp4
    06:03
  • 05 - Applying the rest of the exclusions.mp4
    04:57
  • 06 - Operations in code.mp4
    03:52
  • 07 - Making a data reduction diagram.mp4
    04:35
  • 08 - Generating exposure.mp4
    04:43
  • 09 - Generating outcome variables.mp4
    03:32
  • 01 - Generating the age variables.mp4
    04:18
  • 02 - Generating the smoking variables.mp4
    04:36
  • 03 - Finalizing the analytic data set.mp4
    05:46
  • 04 - What is Table 1.mp4
    04:26
  • 05 - Reviewing categorical variable distribution.mp4
    06:15
  • 06 - Reviewing continuous variable distribution.mp4
    06:29
  • 01 - Preparing categorical Table 1 shell.mp4
    06:10
  • 02 - Preparing continuous Table 1 shell.mp4
    02:46
  • 03 - Adding overall frequencies to categorical Table 1.mp4
    04:59
  • 04 - Making a frequency macro.mp4
    04:08
  • 05 - Adding overall frequencies to continuous Table 1.mp4
    03:04
  • 06 - Completing categorical Table 1.mp4
    07:07
  • 07 - Completing continuous Table 1.mp4
    05:47
  • 01 - Three truths about using weights.mp4
    04:58
  • 02 - Conducting a descriptive weighted analysis.mp4
    07:50
  • 03 - Why conduct bivariate tests.mp4
    05:08
  • 04 - Adding categorical bivariate tests to Table 1.mp4
    07:17
  • 05 - Introduction to ANOVA and linear regression code.mp4
    02:43
  • 06 - Adding continuous bivariate tests to Table 1.mp4
    07:25
  • 01 - Review of the metadata.mp4
    06:11
  • 02 - Uses of metadata.mp4
    05:26
  • 03 - Review of the process.mp4
    03:39
  • 04 - Next steps in the BRFSS analysis.mp4
    05:41

    • More details

    Course Overview

    Learn to analyze behavioral health data using R with this comprehensive guide to the BRFSS dataset. Master epidemiological analysis techniques, data visualization, and scientific documentation for public health research.

    What You'll Learn

    • Perform cross-sectional analysis on BRFSS data using R
    • Create data dictionaries and handle metadata effectively
    • Generate and interpret Table 1 for scientific publications

    Who This Is For

    • Public health professionals analyzing population data
    • Data scientists working with healthcare datasets
    • Medical researchers conducting epidemiological studies

    Key Benefits

    • Hands-on experience with real-world BRFSS data
    • Learn to document analysis for scientific publication
    • Master weighted analysis and bivariate testing

    Curriculum Highlights

    1. BRFSS fundamentals and ethical considerations
    2. Metadata design and confounder analysis
    3. Data preparation and descriptive analytics