Pattern mixture models for the analysis of repeated attempt designs.

ABSTRACT: It is not uncommon in follow-up studies to make multiple attempts to collect a measurement after baseline. Recording whether these attempts are successful or not provides useful information for the purposes of assessing the missing at random (MAR) assumption and facilitating missing not at random (MNAR) modeling. This is because measurements from subjects who provide this data after multiple failed attempts may differ from those who provide the measurement after fewer attempts. This type of "continuum of resistance" to providing a measurement has hitherto been modeled in a selection model framework, where the outcome data is modeled jointly with the success or failure of the attempts given these outcomes. Here, we present a pattern mixture approach to model this type of data. We re-analyze

SUBMITTER: Daniels MJ 

PROVIDER: S-EPMC4836559 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature