Average treatment effect in cluster-randomized trials with outcome misclassification and non-random validation subset

Music City Center 

In ASPIRE, a cluster-randomized trial, pediatric primary care clinics receive either facilitation or no facilitation for delivering a secure firearm program. Under this program, clinicians provide both counseling and free gun locks to parents. Randomization should enable non-parametric estimation of the ATE, but clinicians document their own delivery of the program, which may not reflect true delivery. In a follow-up study to address this classification error, parents are asked to validate clinicians' documentation, but only a fraction volunteer. In this setting where a non-random internal validation set is available, we demonstrate that it is possible to use the relationship between gold-standard (parent) and silver-standard (clinician) measures to target the ATE without bias. Moreover, we show that our method is valid even when selection into the validation sample depends on the true outcome. Simulation studies demonstrate acceptable finite sample performance of our estimators with cluster-robust variance expressions in the presence of misclassification and selection bias in the validation set. We apply our methods to ASPIRE to assess the impact of facilitation on program delivery.

cluster-randomized trial

measurement error

selection bias

causal inference 

ENAR