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Robust Clustering with Subpopulation-specific Deviations.
- Source :
-
Journal of the American Statistical Association [J Am Stat Assoc] 2020; Vol. 115 (530), pp. 521-537. Date of Electronic Publication: 2019 Jun 19. - Publication Year :
- 2020
-
Abstract
- The National Birth Defects Prevention Study (NBDPS) is a case-control study of birth defects conducted across 10 U.S. states. Researchers are interested in characterizing the etiologic role of maternal diet, collected using a food frequency questionnaire. Because diet is multi-dimensional, dimension reduction methods such as cluster analysis are often used to summarize dietary patterns. In a large, heterogeneous population, traditional clustering methods, such as latent class analysis, used to estimate dietary patterns can produce a large number of clusters due to a variety of factors, including study size and regional diversity. These factors result in a loss of interpretability of patterns that may differ due to minor consumption changes. Based on adaptation of the local partition process, we propose a new method, Robust Profile Clustering, to handle these data complexities. Here, participants may be clustered at two levels: (1) globally, where women are assigned to an overall population-level cluster via an overfitted finite mixture model, and (2) locally, where regional variations in diet are accommodated via a beta-Bernoulli process dependent on subpopulation differences. We use our method to analyze the NBDPS data, deriving pre-pregnancy dietary patterns for women in the NBDPS while accounting for regional variability.
Details
- Language :
- English
- ISSN :
- 0162-1459
- Volume :
- 115
- Issue :
- 530
- Database :
- MEDLINE
- Journal :
- Journal of the American Statistical Association
- Publication Type :
- Academic Journal
- Accession number :
- 32952235
- Full Text :
- https://doi.org/10.1080/01621459.2019.1611583