TY - JOUR AU - Moore, Camille M. AU - MaWhinney, Samantha AU - Carlson, Nichole E. AU - Kreidler, Sarah PY - 2020 DA - 2020/10/07 TI - A Bayesian natural cubic B-spline varying coefficient method for non-ignorable dropout JO - BMC Medical Research Methodology SP - 250 VL - 20 IS - 1 AB - Dropout is a common problem in longitudinal clinical trials and cohort studies, and is of particular concern when dropout occurs for reasons that may be related to the outcome of interest. This paper reviews common parametric models to account for dropout and introduces a Bayesian semi-parametric varying coefficient model for exponential family longitudinal data with non-ignorable dropout. SN - 1471-2288 UR - https://doi.org/10.1186/s12874-020-01135-3 DO - 10.1186/s12874-020-01135-3 ID - Moore2020 ER -