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Park SY, Xiao L, Willbur JD, et al. A joint design for functional data with application to scheduling ultrasound scans. Comput Stat Data Anal. 2018;122:101-114doi: 10.1016/j.csda.2018.01.009.
Park, S. Y., Xiao, L., Willbur, J. D., Staicu, A. M., & Jumbe, N. L. (2018). A joint design for functional data with application to scheduling ultrasound scans. Computational statistics & data analysis, 122101-114. https://doi.org/10.1016/j.csda.2018.01.009
Park, So Young, et al. "A joint design for functional data with application to scheduling ultrasound scans." Computational statistics & data analysis vol. 122 (2018): 101-114. doi: https://doi.org/10.1016/j.csda.2018.01.009
Park SY, Xiao L, Willbur JD, Staicu AM, Jumbe NL. A joint design for functional data with application to scheduling ultrasound scans. Comput Stat Data Anal. 2018 Jun;122:101-114. doi: 10.1016/j.csda.2018.01.009. PMID: 29861518; PMCID: PMC5840761.
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Comput Stat Data Anal. 2018 Jun;122:101-114. doi: 10.1016/j.csda.2018.01.009.

A joint design for functional data with application to scheduling ultrasound scans.

Computational statistics & data analysis

So Young Park, Luo Xiao, Jayson D Willbur, Ana-Maria Staicu, N L'ntshotsholé Jumbe

Affiliations

  1. Eli Lilly and Company, Indianapolis, IN, USA.
  2. North Carolina State University, Raleigh, NC, USA.
  3. Metrum Research Group LLC, Tariffville, CT, USA.
  4. Bill & Melinda Gates Foundation, Seattle, WA, USA.

PMID: 29861518 PMCID: PMC5840761 DOI: 10.1016/j.csda.2018.01.009

Abstract

A joint design for sampling functional data is proposed to achieve optimal prediction of both functional data and a scalar outcome. The motivating application is fetal growth, where the objective is to determine the optimal times to collect ultrasound measurements in order to recover fetal growth trajectories and to predict child birth outcomes. The joint design is formulated using an optimization criterion and implemented in a pilot study. Performance of the proposed design is evaluated via simulation study and application to fetal ultrasound data.

Keywords: Covariance function; Fetal growth; Functional data analysis; Longitudinal data; Prediction

References

  1. J Am Stat Assoc. 2012 Dec 21;107(500):1297-1309 - PubMed
  2. Electron J Stat. 2012 Jan 1;6:323-353 - PubMed
  3. Biometrics. 2014 Dec;70(4):802-11 - PubMed
  4. Biostatistics. 2009 Jan;10(1):32-45 - PubMed
  5. J Am Stat Assoc. 2006 Dec 1;101(476):1352-1364 - PubMed
  6. Biometrics. 2010 Mar;66(1):61-9 - PubMed
  7. Neuroimage. 2009 Aug 1;47(1):184-93 - PubMed
  8. J R Stat Soc Ser C Appl Stat. 2016 Feb;65(2):215-236 - PubMed
  9. Electron J Stat. 2010;4:1022-1054 - PubMed
  10. Stat (Int Stat Inst). 2015;4(1):212-226 - PubMed
  11. Biometrics. 2018 Mar;74(1):229-238 - PubMed
  12. Stat Med. 2012 Nov 20;31(26):3223-40 - PubMed
  13. Biostatistics. 2015 Apr;16(2):352-67 - PubMed

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