BACKGROUND: Noncompliance to treatment assignment is an inevitable occurrence in @entity922 ( @entity922 ). @entity2045 ( @entity2045 ) is generally considered the best method for addressing noncompliance in @entity922 . Alternatives to @entity2045 exist, including per protocol (PP), @entity15296 ( @entity15296 ), and instrumental variables (IV). These three methods define @entity1 compliance dichotomously, but partial compliance is a common occurrence in @entity922 . By defining a threshold, above which a @entity1 is called a complier, PP, @entity15296 and IV can be used, but the resulting loss of information may affect their performance. Trials with factorial designs may experience higher rates of noncompliance due to the heavier burden that @entity1 experience by being assigned to multiple experimental treatments. METHODS: Using simulations, we assessed the performance of @entity2045 , PP, @entity15296 , and IV in both the partial compliance setting and in a 2-by-2 factorial design with increased @entity1 burden for those randomized to both active treatments. RESULTS: The bias, mean squared error, and type I error rates of the IV method after dichotomizing partial compliance were heavily inflated. The performance of all four methods depended on the level of noncompliance present, with higher average noncompliance leading to poorer performance. PP and @entity15296 showed improved bias and power relative to @entity2045 without inflating the type I error beyond acceptable limits. However, the PP and @entity15296 heavily inflated the type I error rates when @entity1 compliance was affected by the @entity1 ' general health. CONCLUSIONS: There are consequences for dichotomizing compliance information to make it fit into well-known methods. The results suggest the need for a method of estimating treatment effects that can utilize partial compliance information.

Dichotomizing partial compliance and increased XXXX burden in factorial designs: the performance of four noncompliance methods.

@entity2045 :: ('MESH:D009207', 'Disease') :: ['Intention to treat', 'ITT'] @entity1 :: ('9606', 'Species') :: ['participants', 'participant'] @entity15296 :: ('MESH:D019553', 'Disease') :: ['as treated', 'AT'] @entity922 :: ('MESH:D013568', 'Disease') :: ['randomized clinical trials', 'RCTs']
@entity1 :: (9606,Species) :: ['participant']
