Course information

We will be working with the NHANES dataset curated by the textbook, Functional Data Analysis with R.

Schedule

Week	Date	Location	Topic	Reading	Activity
1	4/3 @4pm	VPT 615B	Intro	Best practices for analyzing large-scale health data from wearables and smartphone apps
2	4/11 @1pm	Virtual	Research Questions	Functional Data Analysis with R, Section 1.2.1	Use R to explore NHANES data Reproduce Figure 1.1
3	4/17 @4pm	VPT 615B	Prepare Data	acc: An R package to process, visualize, and analyze accelerometer data Accelerometer Data Collection and Processing Criteria to Assess Physical Activity and Other Outcomes: A Systematic Review and Practical Considerations	Use some of the functions in acc to simulate and explore accelerometer data
4	4/24 @4pm	Virtual	Prepare Data: Missing data	A framework for handling missing accelerometer outcome data in trials Lecture from BSTA 513	TBD
5	5/1 @4pm	Virtual	Analyze Data	A Review of Statistical Analyses on Physical Activity Data Collected from Accelerometers	TBD: maybe nothing, maybe performing a similar summary
6	No class this week		Analyze Data 1: Cross-sectional studies	The associations of physical activity patterns and the triglyceride-glucose index in US adults: a secondary data analysis of NHANES (2007–2018)
7	5/15 @4pm	VPT 615B	Analyze Data 2: Longitudinal Data Analysis	Association of Longitudinal Activity Measures and Diabetes Risk: An Analysis From the National Institutes of Health All of Us Research Program
8	5/22 @4pm	Virtual	Analyze Data 3: Functional Data Analysis	Youtube Video on Intro to Functional Data Analysis (~23 min) Functional Data Analysis with R, Section 4.0-4.1	Work through the R code for Section 4.0-4.1
9	5/29 @4pm	VPT 615B	Analyze Data 3: Functional Data Analysis	Functional Data Analysis with R, Section 4.2-4.3	Work through the R code for Section 4.2-4.3
10	6/5 @4pm	Virtual	Share Results	TBD
11