Mendelian randomization is a special type of instrumental variable analysis. Its application in the medical field increases in popularity because of its obvious advantages and the rapid development of genomics. This article aimed to introduce the basic concepts, principles, common methods, and limitations of Mendelian randomization. It is expected to provide guidance for researchers to conduct Mendelian randomization studies.
Objective To explore the differences between large and small studies in rare events meta-analysis. Methods Empirical data were collected from The Cochrane Systematic Review Database from January 2003 to May 2018. Meta-analyses with rare events, binary outcomes involving at least 5 studies, and at least 1 large study were screened. Peto and classical ORs were used to compare the magnitude, direction and P-value. Results A total of 214 meta-analyses were included. Among 214 pairs of ORs of large and small studies, 66 pairs (30.84%) were inconsistent in the direction of ORs based on Peto OR (Kappa =0.33), and 69 pairs (32.24%) were inconsistent in the direction of ORs based on classical OR. The Peto ORs resulted in smaller P-values compared to classic ORs in a substantial (83.18%) number of cases. Conclusion There are considerable differences between large and small studies in the results of meta-analysis of rare events.
Causal inference is one of the main goals of medical research. However, due to the lack of an in-depth understanding of the theory of causal inference, researchers tend to blindly use multiple statistical methods to analyse the same question to enhance the credibility of the results, which leads to problems in interpretation of the analysis results. Based on the three basic concepts of potential outcomes, causal effects, and distributive mechanisms of the causal inference counterfactual framework, this paper introduced six main target effects in causal inference and discussed their comparability to help researchers understand the principle of causal inference and correctly interpret and compare research results to avoid misleading conclusions.