Suplemental Materials for Unreliable Continuous Treatment Indicators in Propensity Score Analysis

Propensity score analyses (PSA) of continuous treatments often operationalize the treatment as a multi-indicator composite, and its composite reliability is unreported. Latent variables or factor scores accounting for this unreliability are seldom used as alternatives to compo- sites. This study examines the effects of the unreliability of indicators of a latent treatment in PSA using the generalized propensity score (GPS). A Monte Carlo simulation study was conducted varying composite reliability, continuous treatment representation, variability of factor loadings, sample size, and number of treatment indicators to assess whether Average Treatment Effect (ATE) estimates differed in their relative bias, Root Mean Squared Error, and coverage rates.

倾向得分分析（PSA）在处理连续治疗方法时，往往将治疗方法操作化为一个包含多个指标的综合体，而其综合信度却鲜有报道。在补偿这种不可靠性的情况下，很少使用潜在变量或因子分数作为复合指标的替代方案。本研究利用广义倾向得分（GPS）考察了潜在治疗方法指标不可靠性在PSA中的影响。通过进行蒙特卡洛模拟研究，本研究调整了综合信度、连续治疗方法表示、因子载荷的变异性、样本量以及治疗指标的数量，以评估平均处理效应（ATE）估计的相对偏差、均方根误差和覆盖率是否存在差异。