No abstract

Object In randomized clinical trials of subarachnoid hemorrhage (SAH) in which the primary clinical outcomes are ordinal, it has been common practice to dichotomize the ordinal outcome scale into favorable versus unfavorable outcome. Using this strategy may increase sample sizes by reducing statistical power. Authors of the present study used SAH clinical trial data to determine if a sliding dichotomy would improve statistical power. Methods Available individual patient data from tirilazad (3552 patients), clazosentan (the Clazosentan to Overcome Neurological Ischemia and Infarction Occurring After Subarachnoid Hemorrhage trial [CONSCIOUS-1], 413 patients), and subarachnoid aneurysm trials (the International Subarachnoid Aneurysm Trial [ISAT], 2089 patients) were analyzed. Treatment effect sizes were examined using conventional fixed dichotomy, sliding dichotomy (logical or median split methods), or proportional odds modeling. Whether sliding dichotomy affected the difference in outcomes between the several age and neurological grade groups was also evaluated. Results In the tirilazad data, there was no significant effect of treatment on outcome (fixed dichotomy: OR = 0.92, 95% CI 0.80–1.07; and sliding dichotomy: OR = 1.02, 95% CI 0.87–1.19). Sliding dichotomy reversed and increased the difference in outcome in favor of the placebo over clazosentan (fixed dichotomy: OR = 1.06, 95% CI 0.65–1.74; and sliding dichotomy: OR = 0.85, 95% CI 0.52–1.39). In the ISAT data, sliding dichotomy produced identical odds ratios compared with fixed dichotomy (fixed dichotomy vs sliding dichotomy, respectively: OR = 0.67, 95% CI 0.55–0.82 vs OR = 0.67, 95% CI 0.53–0.85). When considering the tirilazad and CONSCIOUS-1 groups based on age or World Federation of Neurosurgical Societies grade, no consistent effects of sliding dichotomy compared with fixed dichotomy were observed. Conclusions There were differences among fixed dichotomy, sliding dichotomy, and proportional odds models in the magnitude and precision of odds ratios, but these differences were not as substantial as those seen when these methods were used in other conditions such as head injury. This finding suggests the need for different outcome scales for SAH.

No abstract

Penelitian ini menerapkan metode resampling pada pasangan data pengamatan untuk mendapatkan estimasi parameter model regresi dengan metode resampling bootstrap dan jackknife. Metode bootstrap didasarkan teknik pengambilan sampel dengan pengembalian, sedangkan Jackknife didasarkan penghapusan satu sampel pada setiap pengambilan sampel dengan pengembalian. Berdasarkan data simulasi, ditentukan bias  estimasi parameter dan panjang interval dengan tingkat kepercayaan 95% serta standard error. Selanjutnya, dibandingkan reliabilitas yang diterapkan pada kedua metode tersebut. Berdasarkan bias, panjang interval, dan standard error estimasi parameter model regresi, metode resampling bootstrap lebih kecil daripada metode resampling jackknife.Kata Kunci: resampling bootstrap dan jackknife, bias, standard error, dan panjang   interval.