In systematic reviews and meta-analyses, time-to-event outcomes were mostly analysed using hazard ratios (HR). It was neglected transformation of the data so that some wrong outcomes were gained. This study introduces how to use Stata and R software to calculate the HR correctly if the report presents HR and confidence intervals were gained.
Meta-analysis is the quantitative, scientific synthesis of research results. Fixed-effect and random-effect models are two popular statistical models for meta-analysis. The selection of the appropriate model is crucial. In this paper, we introduce some noval views of models and explain key assumptions, hypothesis, and interpretation of each model. We conclude with a discussion of factors to consider in model selection, and provide a recommendation on selection of appropriate statistical models for traditional meta-analysis.
The paper presents two statistical methods to compare summary estimates of different subgroups in meta-analysis. It also shows how to use Z test and meta-regression model with dichotomous data and continuous data in R software to explain the similarities and differences between the two statistical methods by examples.
The PRISMA aims to enhance the transparency and reporting quality of systematic reviews. PRISMA 2020 is an update version of PRISMA 2009, which was published in BMJ in March, 2021. This article compared the PRISMA 2020 and PRISMA 2009, interpreted PRISMA 2020 with representative examples, aiming to help Chinese scholars better understand and apply this reporting guideline, thus to improve the reporting quality of systematic reviews.