Scholarlink

<p>Weighted Quantile Sum (WQS) regression is a statistical method for quantifying the association between multiple possibly correlated predictors and a health outcome, estimating both the joint effect of the predictors as well as their individual contributions to the total effect. WQS has become one of the most popular and widely used approaches for investigating complex mixtures in environmental epidemiology, yet its implementation has been largely restricted to R users. In this paper we present <i>wqsreg</i>, the first Stata command for WQS regression, implemented for continuous, binary and count outcomes. We describe command’s architecture and present an application of the command on exposome data exploring the association between 38 exposures and a continuous outcome. <i>Wqsreg</i> provides a user-friendly command for WQS regression that integrates several flexible components of the framework such as bootstrap, training/validation splitting, and repeated holdout procedures. <i>Wqsreg</i> returns regression estimates as well as graphical displays of the individual weights. It requires Stata version 11 or higher and is freely available on GitHub [<a href="https://github.com/PonzanoMarta/wqsreg">https://github.com/PonzanoMarta/wqsreg</a>]. Given the increasing importance of appropriately exploring complex multidimensional exposures, this contribution will further promote the use of appropriate statistical methods in epidemiological settings with multiple correlated predictors.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Wqsreg: a Stata command for weighted quantile sum regression

  • 期刊论文

  • 发表日期：

    2026年6月25日

查看全文
  • Marta Ponzano,
  • Stefano Renzetti,
  • Chris Gennings,
  • Andrea Bellavia

摘要

Weighted Quantile Sum (WQS) regression is a statistical method for quantifying the association between multiple possibly correlated predictors and a health outcome, estimating both the joint effect of the predictors as well as their individual contributions to the total effect. WQS has become one of the most popular and widely used approaches for investigating complex mixtures in environmental epidemiology, yet its implementation has been largely restricted to R users. In this paper we present wqsreg, the first Stata command for WQS regression, implemented for continuous, binary and count outcomes. We describe command’s architecture and present an application of the command on exposome data exploring the association between 38 exposures and a continuous outcome. Wqsreg provides a user-friendly command for WQS regression that integrates several flexible components of the framework such as bootstrap, training/validation splitting, and repeated holdout procedures. Wqsreg returns regression estimates as well as graphical displays of the individual weights. It requires Stata version 11 or higher and is freely available on GitHub [https://github.com/PonzanoMarta/wqsreg]. Given the increasing importance of appropriately exploring complex multidimensional exposures, this contribution will further promote the use of appropriate statistical methods in epidemiological settings with multiple correlated predictors.