Spss r plugin

Categorical variables were reported as number (n) and proportion (%) and compared using Pearson’s χ² analysis. Continuous variables were reported as median and range. The RFS and OS were calculated using the Kaplan–Meier method and compared using the log-rank test. The Cox proportional hazards model was used to identify independent risk factors associated with RFS and OS by multivariate analysis. A P value < 0.05 was set as the significance threshold.
To balance the background risks between the two study groups, we performed 1:1 propensity score matching (PSM) using a caliper of 0.1 and to include age, gender, etiology, alanine aminotransferase, portal hypertension, Child–Pugh grade, AFP, extent of hepatectomy, intraoperative blood transfusion, histological severity of cirrhosis, microvascular invasion, and tumor differentiation. The PSM model was generated using the PSM program through the SPSS R-Plugin. The analysis applied single nearest-neighbor matching.
For all tests, a 2-tailed P < 0.05 was considered statistically significant. Statistical analysis was performed using the SPSS 26 statistical software (SPSS, Inc., Chicago, IL, USA).

Continuous variables were expressed as median (range). A Kolmogorov–Smirnov test was used to check the normality distribution of continuous data and then the independent samples T test or Mann–Whitney U test was applied. Categorical variables were expressed as absolute numbers (percentages) and compared using the χ²-test or Fisher’s exact test as appropriate. Overall survival was calculated using the Kaplan–Meier method. The difference between survival rates was assessed by the log-rank test. Univariate and multivariate analysis of prognostic factors for long-term survival in PS matched cohort were carried out using the Cox regression model. Significant prognostic factors identified by univariate analysis were incorporated into multivariate analysis and further assessed as independent prognostic factors.
Statistical analysis was carried out using SPSS version 23.0 (SPSS Inc., Chicago, IL, USA). Propensity score analysis and matching were performed with the psmatching program. All analyses were performed in R through the SPSS R-Plugin (SPSS R Essentials). P value ≤ 0.05 was considered statistically significant.