Functional data analysis to characterize disease patterns in frequent longitudinal data: application to bacterial vaginal microbiota patterns using weekly Nugent scores and identification of pattern-specific risk factors
Published 2023 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Functional data analysis to characterize disease patterns in frequent longitudinal data: application to bacterial vaginal microbiota patterns using weekly Nugent scores and identification of pattern-specific risk factors
Authors
Keywords
-
Journal
BMC Medical Research Methodology
Volume 23, Issue 1, Pages -
Publisher
Springer Science and Business Media LLC
Online
2023-10-27
DOI
10.1186/s12874-023-02063-8
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Modeling the temporal dynamics of cervicovaginal microbiota identifies targets that may promote reproductive health
- (2021) Alexander Munoz et al. Microbiome
- Differential effects of depot medroxyprogesterone acetate administration on vaginal microbiome in Hispanic White and Black women
- (2019) Liying Yang et al. Emerging Microbes & Infections
- Risk and protective factors associated with BV chronicity among women in Rakai, Uganda
- (2019) Marie E Thoma et al. SEXUALLY TRANSMITTED INFECTIONS
- Impact of contraceptive initiation on vaginal microbiota
- (2018) Sharon L. Achilles et al. AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY
- Pharmacokinetic, biologic and epidemiologic differences in MPA- and NET-based progestin-only injectable contraceptives relative to the potential impact on HIV acquisition in women
- (2018) Renee Heffron et al. CONTRACEPTION
- High-dimensional functional time series forecasting: An application to age-specific mortality rates
- (2018) Yuan Gao et al. JOURNAL OF MULTIVARIATE ANALYSIS
- Pathogenesis of Bacterial Vaginosis: Discussion of Current Hypotheses
- (2016) Christina A. Muzny et al. JOURNAL OF INFECTIOUS DISEASES
- Functional Data Analysis
- (2016) Jane-Ling Wang et al. Annual Review of Statistics and Its Application
- Ecological Momentary Assessment of Illicit Drug Use Compared to Biological and Self-Reported Methods
- (2016) Beth S. Linas et al. JMIR mHealth and uHealth
- Utilizing mHealth methods to identify patterns of high risk illicit drug use
- (2015) Beth S. Linas et al. DRUG AND ALCOHOL DEPENDENCE
- Monitoring 6-Month Trajectory of Grip Strength Improves the Prediction of Long-Term Change in Grip Strength in Disabled Older Women
- (2014) Qian-Li Xue et al. JOURNALS OF GERONTOLOGY SERIES A-BIOLOGICAL SCIENCES AND MEDICAL SCIENCES
- A mixture of transition models for heterogeneous longitudinal ordinal data: with applications to longitudinal bacterial vaginosis data
- (2014) Kyeongmi Cheon et al. STATISTICS IN MEDICINE
- A survey of functional principal component analysis
- (2013) Han Lin Shang AStA-Advances in Statistical Analysis
- Daily temporal dynamics of vaginal microbiota before, during and after episodes of bacterial vaginosis
- (2013) Jacques Ravel et al. Microbiome
- Temporal Dynamics of the Human Vaginal Microbiota
- (2012) P. Gajer et al. Science Translational Medicine
- The Natural History of Bacterial Vaginosis Diagnosed by Gram Stain Among Women in Rakai, Uganda
- (2011) Marie E. Thoma et al. SEXUALLY TRANSMITTED DISEASES
- Longitudinal Changes in Vaginal Microbiota Composition Assessed by Gram Stain Among Never Sexually Active Pre- and Postmenarcheal Adolescents in Rakai, Uganda
- (2010) Marie E. Thoma et al. Journal of Pediatric and Adolescent Gynecology
- Bacterial Vaginosis: Identifying Research Gaps Proceedings of a Workshop Sponsored by DHHS/NIH/NIAID
- (2010) Jeanne M. Marrazzo et al. SEXUALLY TRANSMITTED DISEASES
- The Short-term Variability of Bacterial Vaginosis Diagnosed by Nugent Gram Stain Criteria Among Sexually Active Women in Rakai, Uganda
- (2010) Marie E. Thoma et al. SEXUALLY TRANSMITTED DISEASES
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreDiscover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversation