On Wednesday 13^th April, a celebration was held to mark the 30^th anniversary since the publication of the landmark paper “Meta-analysis in clinical trials” by DerSimonian & Laird (1986, Controlled Clinical Trials 7, 177-188). The paper is one of the most highly cited research publications. It introduces the now standard random-effects model for meta-analysis, a variety of estimation methods, and successfully applies these to a variety of real datasets.

Dr Dan Jackson, Senior Investigator Statistician from the MRC Biostatistics Unit (BSU) is significantly involved in extending the work of DerSimonian and Laird’s Methodology. In particular, he has developed multivariate and network meta-analysis extensions, as well as developing new methods for calculating confidence intervals for the between-study variance parameter. He is part of a growing, multi-skilled working group looking into network meta-analysis. Working with Martin Law (BSU), Dr Ian White (BSU), Dr Sylwia Bujkiewicz (University of Leicester) and Dr Richard Riley (Keele University), he is developing a new version of DerSimonian and Laird’s methodology that can be applied to multivariate network meta-analysis datasets, so that multiple treatments and comparisons can be included in one, single analysis.

Dan was one of the key organisers of the special anniversary event that took place at University College London. The celebration brought together statistical scientists from across the country and included talks by Dr Julian Higgins (University of Bristol), Dr Kerry Dawn (University of Liverpool), Dr Richard Riley (Keele University) and Dr Theo Stijnen (Leiden University Medical Centre). It was a fantastic event for all involved, and was attended by both Nan Laird and Rebecca DerSimonian. Dan said “The publication of the DerSimonian and Laird paper was an important landmark for all involved in meta-analysis and methods for systematic reviews. I first became aware of it fifteen years ago when I began my PhD looking into the impact of publication bias on meta-analysis. Who knows what the next 30 years could bring for meta-analysis research?”