2.6. Statistical analyses
This protocol is extracted from research article:
Impact of surgical margin on survival in extremity soft tissue sarcoma
Medicine (Baltimore), Jan 22, 2021; DOI: 10.1097/MD.0000000000024124

We used Higgins I2 statistics to determine the percentage of the total variation across studies due to heterogeneity. The I2 value ranges from 0% (no observed heterogeneity) to 100% (maximal heterogeneity). An I2 value >50% may be considered to represent substantial heterogeneity.[11] Pooled HRs were analyzed using an inverse variance weighting method, and either the random- or fixed-effect model was chosen according to heterogeneity. A forest plot was used to displace the meta-analysis data. The point estimate for the HR was represented by a square, and the CI for each study was represented by a horizontal line. The size of the square corresponds to the weight of the study in the meta-analysis, with larger shapes assigned to studies with larger sample sizes or data of better quality. A sensitivity analysis was used to determine the influence of each individual study on the summary results by repeating the random-effects meta-analysis after omitting 1 study at a time. For identifying publication bias, the Begg funnel plot was used. All statistical analyses in this study were performed using R version 3.1.2 (meta for packages). A P value <.05 was considered statistically significant.

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