With reference to a single mediator context, this brief report presents a model-based strategy to estimate counterfactual direct and indirect effects when the response variable is ordinal and the mediator is binary. Postulating a logistic regression model for the mediator and a cumulative logit model for the outcome, the exact parametric formulation of the causal effects is presented, thereby extending previous work that only contained approximated results. The identification conditions are equivalent to the ones already established in the literature. The effects can be estimated by making use of standard statistical software and standard errors can be computed via a bootstrap algorithm. To make the methodology accessible, routines to implement the proposal in R are presented in the Appendix. A natural effect model coherent with the postulated data generating mechanism is also derived.
翻译:就单一调解人而言,本简要报告提出了一个基于示范战略,用以估计反应变数为正态而调解人为二进制时的反实际直接和间接影响;为调解人设定后勤回归模型和结果累积日志模型,对因果关系作出精确的参数描述,从而扩大以前只包含近似结果的工作;识别条件与文献中已经确立的条件相当;通过使用标准统计软件可以估计影响,标准错误可以通过陷阱算法计算;为便于使用方法,附录中列出了执行R提案的例行程序;还提出了与假设的生成数据机制相一致的自然效应模型。