TY - JOUR T1 - Identifying and quantifying variation between healthcare organisations and geographical regions: using mixed-effects models JF - BMJ Quality & Safety JO - BMJ Qual Saf SP - 1032 LP - 1038 DO - 10.1136/bmjqs-2018-009165 VL - 28 IS - 12 AU - Gary Abel AU - Marc N Elliott Y1 - 2019/12/01 UR - http://qualitysafety.bmj.com/content/28/12/1032.abstract N2 - When the degree of variation between healthcare organisations or geographical regions is quantified, there is often a failure to account for the role of chance, which can lead to an overestimation of the true variation. Mixed-effects models account for the role of chance and estimate the true/underlying variation between organisations or regions. In this paper, we explore how a random intercept model can be applied to rate or proportion indicators and how to interpret the estimated variance parameter. ER -