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wqsreg: A Stata command for weighted quantile sum regression

Author

Listed:
  • Marta Ponzano

    (Università degli studi Link Campus University)

  • Stefano Renzetti

    (Università degli Studi di Parma)

  • Andrea Bellavia

    (Harvard Medical School)

Abstract

Weighted quantile sum (WQS) regression is a statistical method for quantifying the association between a set of possibly correlated predictors and a health outcome, estimating the joint effect of the predictors as well as their individual contributions to the total effect. We present wqsreg, the first Stata command for WQS regression, implemented for continuous, binary, and count outcomes. The execution of the command involves two sequential steps: 1) estimating the weights and constructing the WQS index under specific constraints; and 2) modeling its association with the outcome. wqsreg integrates several flexible components of the framework such as bootstrap, training and validation, and repeated holdout procedures; it returns regression estimates as well as graphical displays of the individual weights. We present an application of the command on exposome data exploring the association between 38 exposures and a continuous outcome while adjusting for a set of covariates. To the best of our knowledge, wqsreg provides the first command to conduct WQS regression in Stata. We anticipate that our contribution will further promote the use of appropriate statistical methods for handling multiple correlated predictors.

Suggested Citation

  • Marta Ponzano & Stefano Renzetti & Andrea Bellavia, "undated". "wqsreg: A Stata command for weighted quantile sum regression," Italian Stata Conference 2026 11, Stata Users Group.
    • Handle: RePEc:boc:ital26:11
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