Clustered encouragement designs with individual noncompliance: bayesian inference with randomization, and application to advance directive forms.

Individual Noncompliance in Clustered Randomized Experiments: Bayesian Inference and Application to an Encouragement Study of Advance Directive Forms

Methods for clustered encouragement design studies with noncompliance and missing data.

Encouragement design studies are particularly useful for estimating the effect of an intervention that cannot itself be randomly administered to some and not to others. They require a randomly selected group receive extra encouragement to undertake the treatment of interest, where the encouragement typically takes the form of additional information or incentives. We consider a "clustered encour...

Randomization Inference in a Group–Randomized Trial of Treatments for Depression: Covariate Adjustment, Noncompliance, and Quantile Effects

In the Prospect Study, in 10 pairs of two primary-care practices, one practice was picked at random to receive a “depression care manager” to treat its depressed patients. Randomization inference, properly performed, reflects the assignment of practices, not patients, to treatment or control. Yet, pertinent data describe individual patients: depression outcomes, baseline covariates, compliance ...

The Method of Randomization for Cluster-Randomized Trials: Challenges of Including Patients with Multiple Chronic Conditions

Cluster-randomized clinical trials (CRT) are trials in which the unit of randomization is not a participant but a group (e.g. healthcare systems or community centers). They are suitable when the intervention applies naturally to the cluster (e.g. healthcare policy); when lack of independence among participants may occur (e.g. nursing home hygiene); or when it is most ethical to apply an interve...

A One-Stage Two-Machine Replacement Strategy Based on the Bayesian Inference Method

In this research, we consider an application of the Bayesian Inferences in machine replacement problem. The application is concerned with the time to replace two machines producing a specific product; each machine doing a special operation on the product when there are manufacturing defects because of failures. A common practice for this kind of problem is to fit a single distribution to the co...