Development of a meta analysis package for Julia

Meta analysis is a widely used statistical technique for pooling diverse study results. Julia does not have a meta analysis package. The goal of this talk is to present the steps and usage of a meta analysis package in pure Julia that I have developed and is in pre-alpha stage. I will explain the steps and processes of implementing fixed-effects and random-effects meta-analysis in Julia and construction of several plotting functions and advanced methods that are unique features of this package.

The goal of this presentation is to present the first ever meta analysis package written entirely in Julia and describe in details the various advanced features in details. Meta analysis is an important technique of data analysis and is widely used in health and medicine for generation of evidence, and it is pivotal technique for evidence based health and widely used in other fields (economics, environmental health, and social sciences among other fields). Julia till date does not have a dedicated package for meta analysis and this package will fill this important gap in the Julia packages database. I have developed a Julia based meta-analysis package and it is in early alpha and I am testing it with my colleagues and students before release. The meta analysis package is written in Julia using a range of other existing packages and implements the meta-analysis techniques described in leading texts. It includes the following features: meta-analysis of single variables, meta-analysis of comparative studies; fixed-effects, random-effects meta analysis that implements DerSimonian-Laird Method and REML methods; testing for heterogeneity; forest and funnel plots; regression tests for publication bias; sensitivity analyses and meta-regression, and multilevel meta-analysis. This package will enable users to conduct meta-analysis of binary variables, continuous variables, time to event, In the presentation, I will present the functions, packages, discuss codes, and experiences in building the package. I will also provide several examples of graphs and different types of data sets. The presentation will end with plans for future developments, and setting up a user community. The presentation will serve as a demonstration and a tutorial on meta-analysis.