Analyzing evidence-based falls prevention data with significant missing information using variable selection after multiple imputation
Author:
Affiliation:
1. The University of Georgia, Athens, GA, USA
2. Renmin University of China, Beijing, People's Republic of China
3. Texas A&M University, College Station, TX, USA
Funder
National Natural Science Foundation of China
NCOA, Lewin Subcontract Agreement
ACL, Prevention and Public Health Fund-NCOA, National Falls Prevention Resource Center Cooperative Agreement Grant
Publisher
Informa UK Limited
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Link
https://www.tandfonline.com/doi/pdf/10.1080/02664763.2021.1985090
Reference40 articles.
1. P. Bühlmann and S. Van De Geer, Statistics for high-dimensional data: Methods, theory and applications, Springer Science & Business Media, 2011.
2. G. Bergen, Falls and fall injuries among adults aged ≥65 years-united states, 2014, MMWR. Morbidity and mortality weekly report 65, 2016.
3. Centers for Disease Control and Prevention. Take a Stand on Falls: What Can Older Adults Do to Prevent Falls? (2017). https://www.cdc.gov/features/older-adult-falls/index.html.
4. Variable selection for multiply-imputed data with application to dioxin exposure study
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