Sample selectivity is a recurrent problem in public health programmes and poses serious challenges to their evaluation. Traditional approaches to handle sample selection tend to rely on restrictive assumptions. The aim of this paper is to illustrate a copula-based selection model to handle sample selection in the evaluation of public health programmes. Motivated by a public health programme to promote physical activity in Leeds (England), we describe the assumptions underlying the copula selection, and its relative advantages compared with commonly used approaches to handle sample selection, such as inverse probability weighting and Heckman’s selection model. We illustrate the methods in the Leeds Let’s Get Active programme and show the implications of method choice for estimating the effect on individual’s physical activity. The programme was associated with increased physical activity overall, but the magnitude of its effect differed according to adjustment method. The copula selection model led to a similar effect to the Heckman’s approach but with relatively narrower 95% confidence intervals. These results remained relatively similar when different model specifications and alternative distributional assumptions were considered. The copula selection model can address important limitations of traditional approaches to address sample selection, such as the Heckman model, and should be considered in the evaluation of public health programmes, where sample selection is likely to be present.

样本选择性是公共卫生项目中反复出现的问题，并对其评估提出了严峻挑战。处理样本选择的传统方法往往依赖于限制性假设。本文的目的是说明一个基于 copula 的选择模型来处理公共卫生项目评估中的样本选择。在利兹（英格兰）促进身体活动的公共卫生计划的推动下，我们描述了 copula 选择背后的假设，以及它与处理样本选择的常用方法（例如逆概率加权和 Heckman 选择模型）相比的相对优势。我们说明了 Leeds Let's Get Active 计划中的方法，并展示了方法选择对估计对个人身体活动的影响的影响。该计划与整体体力活动的增加有关，但其影响的大小因调整方法而异。copula 选择模型产生了与 Heckman 方法类似的效果，但 95% 的置信区间相对较窄。当考虑不同的模型规范和替代分布假设时，这些结果仍然相对相似。copula 选择模型可以解决传统方法来解决样本选择的重要局限性，例如 Heckman 模型，并且在评估可能存在样本选择的公共卫生项目时应予以考虑。copula 选择模型产生了与 Heckman 方法类似的效果，但 95% 的置信区间相对较窄。当考虑不同的模型规范和替代分布假设时，这些结果仍然相对相似。copula 选择模型可以解决传统方法来解决样本选择的重要局限性，例如 Heckman 模型，并且在评估可能存在样本选择的公共卫生项目时应予以考虑。copula 选择模型产生了与 Heckman 方法类似的效果，但 95% 的置信区间相对较窄。当考虑不同的模型规范和替代分布假设时，这些结果仍然相对相似。copula 选择模型可以解决传统方法来解决样本选择的重要局限性，例如 Heckman 模型，并且在评估可能存在样本选择的公共卫生项目时应予以考虑。