Section 1 : Introduction

 		Lecture 1 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM Pdf
Lecture 2 What you should know 0:31
Lecture 3 Introduction to the course 1:22
Lecture 4 How to use the exercise files 0:39

Section 2 : What Is the BRFSS

 		Lecture 5 US risk factors
Lecture 6 Introduction to the BRFSS 2:46
Lecture 7 More on the BRFSS 1:50
Lecture 8 What is a descriptive BRFSS analysis 4:57
Lecture 9 Cross-sectional analysis in the BRFSS 3:52
Lecture 10 Ethical use of BRFSS data 4:38
Lecture 11 BRFSS resources 2:25
Lecture 12 Choosing R for a BRFSS analysis Some considerations 3:51
Lecture 13 Choosing R for a BRFSS analysis More considerations
Lecture 14 Installing R 1:50
Lecture 15 Navigating in R 2:37
Lecture 16 Installing the foreign package 3:8
Lecture 17 Installing necessary packages 3:58

Section 3 : Designing Your Metadata

 		Lecture 18 Uses of a data dictionary 4:35
Lecture 19 How to set up a data dictionary 3:48
Lecture 20 Adding to the data dictionary 6:13
Lecture 21 Understanding confounders 4:24
Lecture 22 Making a web of causation
Lecture 23 Designing confounders Age and smoking 4:42
Lecture 24 Designing confounders Other demographics 4:19
Lecture 25 Designing confounders Other variables used in analysis 4:39

Section 4 : Reading in Data and Applying Exclusions

 		Lecture 26 Reading in BRFSS XPT data 6:57
Lecture 27 Naming conventions 5:38
Lecture 28 Keeping native variables 5:15
Lecture 29 Applying the first exclusion 6:3
Lecture 30 Applying the rest of the exclusions 4:57
Lecture 31 Operations in code 3:52
Lecture 32 Making a data reduction diagram 4:35
Lecture 33 Generating exposure 4:43
Lecture 34 Generating outcome variables

Section 5 : Preparing for Descriptive Analysis

 		Lecture 35 Generating the age variables 4:18
Lecture 36 Generating the smoking variables 4:36
Lecture 37 Finalizing the analytic data set 5:46
Lecture 38 What is Table 1 4:26
Lecture 39 Reviewing categorical variable distribution 6:15
Lecture 40 Reviewing continuous variable distribution 6:29

Section 6 : Conducting Descriptive Analysis

 		Lecture 41 Preparing categorical Table 1 shell 6:10
Lecture 42 Preparing continuous Table 1 shell 2:46
Lecture 43 Adding overall frequencies to categorical Table 1 4:59
Lecture 44 Making a frequency macro 4:8
Lecture 45 Adding overall frequencies to continuous Table 1 3:4
Lecture 46 Completing categorical Table 1 7:7
Lecture 47 Completing continuous Table 1 5:47

Section 7 : Descriptive Analysis Weights and Tests

 		Lecture 48 Three truths about using weights 4:58
Lecture 49 Conducting a descriptive weighted analysis 7:50
Lecture 50 Why conduct bivariate tests 5:8
Lecture 51 Adding categorical bivariate tests to Table 1 7:17
Lecture 52 Introduction to ANOVA and linear regression code 2:43
Lecture 53 Adding continuous bivariate tests to Table 1 7:25

Section 8 : Conclusion

 		Lecture 54 Review of the metadata 6:11
Lecture 55 Uses of metadata 5:26
Lecture 56 Review of the process