The SAS is considered as internationally-known standard software in the field of data processing and statistics, which is also excellent in conducting meta-analysis; however, it require users to have higher technical expertise due to its complex and difficult program coding. Assessing statistical power calculation of significance tests is one of important steps in meta-analysis. Guy Cafri et al., developed a macro (%metapower) for well implement this calculation in SAS. This macro is specifically designed to implement the statistical power calculation of overall results of meta-analysis, heterogenity, and subgroup analysis, which is easy to operate. This article introduces%metapower based on examples.
Meta-analyses include meta-analysis of the published literature (MPL) and meta-analysis of individual patient data (MIPD). Recursive cumulative meta-analysis is a method used to reorganize the secondary analysis data based on original studies thus to ensure a timely update, in addition, it can also be used to analyze the data from longer followup of existing trials. By using this method, with the each newly included or updated study, the change of pooled effect size in each pooled step can be detected, therefore, the bias/heterogeneity and stability of pooled results can be evaluated. In this article, we briefly introduced the concept of recursive cumulative meta-analysis and an example was used to illustrate this method.