This is an archived version of the Handbook. For the current version, please go to or search for this chapter here.  Trim and fill

The ‘trim and fill’ method aims both to identify and correct for funnel plot asymmetry arising from publication bias (Taylor 1998, Duval 2000). The basis of the method is to (1) ‘trim’ (remove) the smaller studies causing funnel plot asymmetry, (2) use the trimmed funnel plot to estimate the true ‘centre’ of the funnel, then (3) replace the omitted studies and their missing ‘counterparts’ around the centre (filling). As well as providing an estimate of the number of missing studies, an adjusted intervention effect is derived by performing a meta-analysis including the filled studies.


The trim and fill method requires no assumptions about the mechanism leading to publication bias, provides an estimate of the number of missing studies, and also provides an estimated intervention effect ‘adjusted’ for the publication bias (based on the filled studies). However, it is built on the strong assumption that there should be a symmetric funnel plot, and there is no guarantee that the adjusted intervention effect matches what would have been observed in the absence of publication bias, since we cannot know the true mechanism for publication bias. Equally importantly, the trim and fill method does not take into account reasons for funnel plot asymmetry other than publication bias. Therefore, ‘corrected’ intervention effect estimates from this method should be interpreted with great caution. The method is known to perform poorly in the presence of substantial between-study heterogeneity (Terrin 2003, Peters 2007). Additionally, estimation and inferences are based on a dataset containing imputed intervention effect estimates. Such estimates, it can be argued, inappropriately contribute information that reduces the uncertainty in the summary intervention effect.