A 'missing not at random' (MNAR) and 'missing at random' (MAR) growth model comparison with a buprenorphinealoxone clinical trial

摘要

AimsTo compare three missing data strategies: (i) the latent growth model that assumes the data are missing at random (MAR) model; (ii) the Diggle-Kenward missing not at random (MNAR) model, where dropout is a function of previous/concurrent urinalysis (UA) submissions; and (iii) the Wu-Carroll MNAR model where dropout is a function of the growth factors.