Author:
Stone Jennifer C.,Habibi Nahal,Aromataris Edoardo
Abstract
Purpose of review
Results of meta-analyses are frequently used to inform clinical practice guidelines and healthcare policy. However, healthcare recommendations derived from these meta-analyses may not be trustworthy if based on the results of biased studies. This literature review aims to provide an up-to-date summary of the state-of-the-art methods for integrating methodological quality data into meta-analyses, also known as bias adjustment, as well as the strengths and weaknesses of current methods. This is essential to ensure meta-analyses are conducted in a way that produces trustworthy and valid results.
Recent findings
This literature review outlines the various bias adjustment methods and some of the advantages and limitations of each. Quality effects modelling has emerged as a promising option, with few limitations and ease of application for meta-analysts.
Summary
This paper outlines what systematic reviewers can expect from different bias adjustment methods, which will be helpful in minimizing the impact of bias on study results and increasing the validity and reliability of findings from meta-analysis.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献