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Nonparametric Bayesian Functional Meta-Regression: Applications in Environmental Epidemiology

Author

Listed:
  • Jaeeun Yu

    (Korea Advanced Institute of Science and Technology)

  • Jinsu Park

    (Korea Advanced Institute of Science and Technology)

  • Taeryon Choi

    (Korea University)

  • Masahiro Hashizume

    (The University of Tokyo)

  • Yoonhee Kim

    (The University of Tokyo)

  • Yasushi Honda

    (University of Tsukuba)

  • Yeonseung Chung

    (Korea Advanced Institute of Science and Technology)

Abstract

Two-stage meta-analysis has been popularly used in epidemiological studies to investigate an association between environmental exposure and health response by analyzing time-series data collected from multiple locations. The first stage estimates the location-specific association, while the second stage pools the associations across locations. The second stage often incorporates location-specific predictors (i.e., meta-predictors) to explain the between-location heterogeneity and is called meta-regression. The existing second-stage meta-regression relies on parametric assumptions and does not accommodate functional meta-predictors and spatial dependency. Motivated by these limitations, our research proposes a nonparametric Bayesian meta-regression which relaxes parametric assumptions and incorporates functional meta-predictors and spatial dependency. The proposed meta-regression is formulated by jointly modeling the association parameters and the functional meta-predictors using Dirichlet process (DP) or local DP mixtures. In doing so, the functional meta-predictors are represented parsimoniously by the coefficients of the orthonormal basis. The proposed models were applied to (1) a temperature–mortality association study and (2) suicide seasonality study, and validated through a simulation study. Supplementary materials accompanying this paper appear online.

Suggested Citation

  • Jaeeun Yu & Jinsu Park & Taeryon Choi & Masahiro Hashizume & Yoonhee Kim & Yasushi Honda & Yeonseung Chung, 2021. "Nonparametric Bayesian Functional Meta-Regression: Applications in Environmental Epidemiology," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(1), pages 45-70, March.
    • Handle: RePEc:spr:jagbes:v:26:y:2021:i:1:d:10.1007_s13253-020-00409-z
    DOI: 10.1007/s13253-020-00409-z
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    References listed on IDEAS

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