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Local polynomial regression for pooled response data

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  • Dewei Wang
  • Xichen Mou
  • Xiang Li
  • Xianzheng Huang

Abstract

We propose local polynomial estimators for the conditional mean of a continuous response when only pooled response data are collected under different pooling designs. Asymptotic properties of these estimators are investigated and compared. Extensive simulation studies are carried out to compare finite sample performance of the proposed estimators under various model settings and pooling strategies. We apply the proposed local polynomial regression methods to two real-life applications to illustrate practical implementation and performance of the estimators for the mean function.

Suggested Citation

  • Dewei Wang & Xichen Mou & Xiang Li & Xianzheng Huang, 2020. "Local polynomial regression for pooled response data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 32(4), pages 814-837, October.
    • Handle: RePEc:taf:gnstxx:v:32:y:2020:i:4:p:814-837
    DOI: 10.1080/10485252.2020.1834104
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    Cited by:

    1. Smith, Lisa C. & Frankenberger, Timothy R., 2022. "Recovering from severe drought in the drylands of Ethiopia: Impact of Comprehensive Resilience Programming," World Development, Elsevier, vol. 156(C).
    2. Dewei Wang & Xichen Mou & Yan Liu, 2022. "Varying‐coefficient regression analysis for pooled biomonitoring," Biometrics, The International Biometric Society, vol. 78(4), pages 1328-1341, December.
    3. Mou, Xichen & Wang, Dewei, 2024. "Additive partially linear model for pooled biomonitoring data," Computational Statistics & Data Analysis, Elsevier, vol. 190(C).

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