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Background and objective: In survival analysis, estimating the survival probability of a population is important, but on the other hand, investigators want to compare the survival experiences of different groups. In such cases, the differences can be illustrated by drawing survival curves, but this will only give a rough idea. Since the data obtained from survival studies contains frequently censored observations some specially designed tests are required in order to compare groups statistically in terms of survival. Methods: In this study, Logrank, Gehan-Wilcoxon, Tarone-Ware, Peto-Peto, Modified Peto-Peto tests and tests belonging to Fleming-Harrington test family with (p, q) values; (1, 0), (0.5, 0.5), (1, 1), (0, 1) ve (0.5, 2) are examined by means of Type I error rate obtained from a simulation study, which is conducted in the cases where the event takes place with equal probability along the follow-up time. Results: As a result of the simulation study, Type I error rate of Logrank test is equal or close to the nominal value. Conclusions: When survival data were generated from lognormal and inverse Gaussian distribution, Type I error rate of Gehan-Wilcoxon, Tarone-Ware, Peto-Peto, Modified Peto-Peto and Fleming-Harrington (1,0) tests were close to the nominal value. (original abstract)
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Bibliografia
- AKBAR, A, PASHA, G. R., (2009). Properties of Kaplan-Meier estimator: group comparison of survival curves. European Journal of Scientific Research, 32 (3), pp. 391-397. https://www.researchgate.net/profile/Atif_Akbar2/publication/255648672_Properties_of_Kaplan- Meier_Estimator_Group_Comparison_of_Survival_Curves/links/549a82f00cf2b80371359dd2.pdf.
- ALLISON, P. D., (2010). Survival analysis using SAS: a practical guide, 2nd edition, SAS Press, North Carolina.
- ALTMAN, D. G., (1991). Practical statistics for medical research, Chapman&Hall, London.
- BLAND, J. M., ALTMAN, D. G., (2004). The logrank test. British Medical Journal, 328, pp. 1073. http://www.bmj.com/content/328/7447/1073.long.
- BELTANGADY, M. S., FRANKOWSKI, R. F., (1989). Effect of unequal censoring on the size and power of the logrank and Wilcoxon types of tests for survival data. Statistics in Medicine, 8 (8), pp. 937-945. https://www.ncbi.nlm.nih.gov/pubmed/2799123.
- BUYSKE, S., FAGERSTROM, R., YING, Z., (2000). A class of weighted logrank tests for survival data when the event is rare. Journal of the American Statistical Association, 95 (449), pp. 249-258. https://www.jstor.org/stable/2669542?seq=1
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Bibliografia
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