Section 1 : Introduction
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Lecture 1 | INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM | |
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Lecture 2 | What you should know | 00:00:31 Duration |
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Lecture 3 | Introduction to the course | 00:01:22 Duration |
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Lecture 4 | How to use the exercise files | 00:00:39 Duration |
Section 2 : What Is the BRFSS
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Lecture 1 | US risk factors | |
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Lecture 2 | Introduction to the BRFSS | 00:02:46 Duration |
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Lecture 3 | More on the BRFSS | 00:01:50 Duration |
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Lecture 4 | What is a descriptive BRFSS analysis | 00:04:57 Duration |
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Lecture 5 | Cross-sectional analysis in the BRFSS | 00:03:52 Duration |
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Lecture 6 | Ethical use of BRFSS data | 00:04:38 Duration |
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Lecture 7 | BRFSS resources | 00:02:25 Duration |
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Lecture 8 | Choosing R for a BRFSS analysis Some considerations | 00:03:51 Duration |
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Lecture 9 | Choosing R for a BRFSS analysis More considerations | |
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Lecture 10 | Installing R | 00:01:50 Duration |
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Lecture 11 | Navigating in R | 00:02:37 Duration |
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Lecture 12 | Installing the foreign package | 00:03:08 Duration |
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Lecture 13 | Installing necessary packages | 00:03:58 Duration |
Section 3 : Designing Your Metadata
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Lecture 1 | Uses of a data dictionary | 00:04:35 Duration |
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Lecture 2 | How to set up a data dictionary | 00:03:48 Duration |
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Lecture 3 | Adding to the data dictionary | 00:06:13 Duration |
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Lecture 4 | Understanding confounders | 00:04:24 Duration |
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Lecture 5 | Making a web of causation | |
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Lecture 6 | Designing confounders Age and smoking | 00:04:42 Duration |
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Lecture 7 | Designing confounders Other demographics | 00:04:19 Duration |
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Lecture 8 | Designing confounders Other variables used in analysis | 00:04:39 Duration |
Section 4 : Reading in Data and Applying Exclusions
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Lecture 1 | Reading in BRFSS XPT data | 00:06:57 Duration |
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Lecture 2 | Naming conventions | 00:05:38 Duration |
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Lecture 3 | Keeping native variables | 00:05:15 Duration |
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Lecture 4 | Applying the first exclusion | 00:06:03 Duration |
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Lecture 5 | Applying the rest of the exclusions | 00:04:57 Duration |
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Lecture 6 | Operations in code | 00:03:52 Duration |
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Lecture 7 | Making a data reduction diagram | 00:04:35 Duration |
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Lecture 8 | Generating exposure | 00:04:43 Duration |
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Lecture 9 | Generating outcome variables |
Section 5 : Preparing for Descriptive Analysis
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Lecture 1 | Generating the age variables | 00:04:18 Duration |
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Lecture 2 | Generating the smoking variables | 00:04:36 Duration |
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Lecture 3 | Finalizing the analytic data set | 00:05:46 Duration |
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Lecture 4 | What is Table 1 | 00:04:26 Duration |
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Lecture 5 | Reviewing categorical variable distribution | 00:06:15 Duration |
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Lecture 6 | Reviewing continuous variable distribution | 00:06:29 Duration |
Section 6 : Conducting Descriptive Analysis
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Lecture 1 | Preparing categorical Table 1 shell | 00:06:10 Duration |
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Lecture 2 | Preparing continuous Table 1 shell | 00:02:46 Duration |
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Lecture 3 | Adding overall frequencies to categorical Table 1 | 00:04:59 Duration |
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Lecture 4 | Making a frequency macro | 00:04:08 Duration |
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Lecture 5 | Adding overall frequencies to continuous Table 1 | 00:03:04 Duration |
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Lecture 6 | Completing categorical Table 1 | 00:07:07 Duration |
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Lecture 7 | Completing continuous Table 1 | 00:05:47 Duration |
Section 7 : Descriptive Analysis Weights and Tests
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Lecture 1 | Three truths about using weights | 00:04:58 Duration |
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Lecture 2 | Conducting a descriptive weighted analysis | 00:07:50 Duration |
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Lecture 3 | Why conduct bivariate tests | 00:05:08 Duration |
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Lecture 4 | Adding categorical bivariate tests to Table 1 | 00:07:17 Duration |
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Lecture 5 | Introduction to ANOVA and linear regression code | 00:02:43 Duration |
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Lecture 6 | Adding continuous bivariate tests to Table 1 | 00:07:25 Duration |
Section 8 : Conclusion
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Lecture 1 | Review of the metadata | 00:06:11 Duration |
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Lecture 2 | Uses of metadata | 00:05:26 Duration |
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Lecture 3 | Review of the process |