Comparison of statistical methods used to meta-analyse results from interrupted time series studies: an empirical study.

ABSTRACT:

Background

The Interrupted Time Series (ITS) is a robust design for evaluating public health and policy interventions or exposures when randomisation may be infeasible. Several statistical methods are available for the analysis and meta-analysis of ITS studies. We sought to empirically compare available methods when applied to real-world ITS data.

Methods

We sourced ITS data from published meta-analyses to create an online data repository. Each dataset was re-analysed using two ITS estimation methods. The level- and slope-change effect estimates (and standard errors) were calculated and combined using fixed-effect and four random-effects meta-analysis methods. We examined differences in meta-analytic level- and slope-change estimates, their 95% confidence intervals, p-values

SUBMITTER: Korevaar E 

PROVIDER: S-EPMC10858609 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature