Single chemical analysis |
Classic linear regression (ordinary least squares) |

Multiple regression |
Classic linear regression (ordinary least squares) |

Visualization, structural equation modeling (SEM), and principal component analysis (PCA) |
Classification and prediction |

Informed sparse PCA and segmented regression |
Classification and prediction |

Bayesian g-formula |
Classification and prediction |

PCA |
Classification and prediction |

Classification and regression trees (CART) |
Classification and prediction |

Bayesian profile regression |
Classification and prediction |

Random forest |
Classification and prediction |

Multivariate adaptive regression splines (MARS) |
Classification and prediction |

Bayesian non-parametric regression |
Classification and prediction |

Bayesian additive regression trees (BART) and negative sparse PCA (NSPCA) |
Classification and prediction |

Conformal predictions |
Classification and prediction |

Bayesian kernel machine regression (BKMR) |
Exposure–response surface estimation |

Building Bayesian networks |
Exposure–response surface estimation |

Exposure surface smoothing (ESS) |
Exposure–response surface estimation |

Modes of action (results presented for *Z* = 0 strata) |
Other |

Feasible solution algorithm (FSA) |
Other |

Exploratory data analysis (EDA) |
Other |

Novel approach and least-angle regression (LARS) |
Variable selection |

Machine learning |
Variable selection |

Two-step variable selection and least absolute shrinkage and selection operator (LASSO) |
Variable selection |

Two-step shrinkage-based regression |
Variable selection |

Factor mixture models |
Variable selection |

Subset and bootstrap |
Variable selection |

Variable selection regression (VSR) |
Variable selection |

Bayesian estimation of weighted sum |
Variable shrinkage strategies |

Shrinkage methods (LASSO/LARS) |
Variable shrinkage strategies |

Weighted quantile sum regression (WQS) |
Variable shrinkage strategies |

LASSO |
Variable shrinkage strategies |