Abstract Number:
1601
Submission Type:
Topic-Contributed Paper Session
Participants:
Fei Xue (1), Xiaojing Sun (1), Haochang Shou (2), Jeff Goldsmith (3), Emily Hector (4), Xiaoxuan Cai (5), Fei Xue (1)
Institutions:
(1) Purdue University, N/A, (2) University of Pennsylvania, N/A, (3) Columbia University, N/A, (4) North Carolina State University, N/A, (5) The Ohio State University, N/A
Chair:
Session Organizer:
Speaker(s):
Session Description:
Short description of the session:
Commercial wearable devices and smartphone apps for monitoring health-related behaviors have proliferated rapidly. Analyzing the data generated by commercial wearables and apps has the potential to alter how we study human behavior and how we intervene to improve health. These datasets are larger and more complex than traditional research studies and bring new statistical challenges.
In recent years, we have seen impressive progress in development of novel statistical methods for wearable device data from various perspectives. In this session, five committed speakers (including four female speakers) will present some modern advances, e.g., how to integrate multidomain device data, how to obtain detailed activity assessment using participant-level daily quantile trajectories, how to develop distributed estimation and inference procedures for intensively measured device data, how to tackle complex missing data from mobile device, and how to integrate multi-resolutional wearable device data. This session will attract audience who are interested in mobile/wearable device, mobile/digital health, data integration, distributed learning, and missing data.
Invited speakers:
1. Haochang Shou, University of Pennsylvania hshou@pennmedicine.upenn.edu
2. Jeff Goldsmith, Columbia University, ajg2202@cumc.columbia.edu
3. Emily Hector, North Carolina State University, ehector@ncsu.edu
4. Xiaoxuan Cai, Ohio State University, cai.1083@osu.edu
5. Fei Xue, Purdue University, feixue@purdue.edu
Tentative presentation titles:
1. Statistical methods for integrating multidomain device data
2. Detailed activity assessment using participant-level daily quantile trajectories
3. New methods for analyzing wearable device data
4. Complex missing data from mobile device
5. Individualized dynamic model for multi-resolutional data
Session format: Chair and 5 speakers
Sponsors:
Committee on Women in Statistics 2
ENAR 3
Section on Risk Analysis 1
Theme:
Statistics and Data Science: Informing Policy and Countering Misinformation
Yes
Applied
No
Estimated Audience Size
Medium (80-150)
I have read and understand that JSM participants must abide by the Participant Guidelines.
Yes
I understand and have communicated to my proposed speakers that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is nonrefundable.
I understand