روش‌های بازنمونه‌گیری بوت استرپ و جک نایف در تحلیل بقای بیماران مبتلا به تالاسمی ماژور

Background and Objectives: A small sample size can influence the results of statistical analysis. A reduction in the sample size may happen due to different reasons, such as loss of information, i.e. existing missing value in some variables. This study aimed to apply bootstrap and jackknife resampling methods in survival analysis of thalassemia major patients. Methods: In this historical cohort study, the data of 296 patients with thalassemia major who were visited at Zafar Clinic, Tehran, from 1994 to 2013 were used. Parametric survival models were used to analyze the data. The log – normal survival model was selected as the best model and then the bootstrap and jackknife resampling algorithms were used for this model. Data analysis was carried out with the STATA 12.0 software. Results: The results of the resampling methods showed that standard errors decreased and confidence intervals were shortened. In addition, the result of the bootstrap and jackknife resampling methods showed that age group and the relationship of the parents (P<0.001) were significant compared with the log-normal model (P>0.900). Conclusion: Comparison of the confidence intervals suggests that the jackknife resampling method can be used when the sample size is small.