Summary: In group sequential clinical trials, there are several sample size re-estimation methods proposed in the literature that allow for change of sample size at the interim analysis. Most of these methods are based on either the conditional error function or the interim effect size. Our simulation studies compared the operating characteristics of three commonly used sample size re-estimation methods. P. Gao, J. H. Ware and C. Mehta [“Sample size re-estimation for adaptive sequential design in clinical trials”, J. Biopharm. Stat. 18, No. 6, 1184–1196 (2008; doi:10.1080/10543400802369053)] extended the CDL method and provided an analytical expression of lower and upper threshold of conditional power where the type I error is preserved. Recently, C. R. Mehta and S. J. Pocock [“ Adaptive increase in sample size when interim results are promising: a practical guide with examples”, Stat. Med. 30, No. 28, 3267–3284 (2010; doi:10.1002/sim.4102)] extensively discussed that the real benefit of the adaptive approach is to invest the sample size resources in stages and increasing the sample size only if the interim results are in the so called “promising zone” which they define in their article. We incorporated this concept in our simulations while comparing the three methods. To test the robustness of these methods, we explored the impact of incorrect variance assumption on the operating characteristics. We found that the operating characteristics of the three methods are very comparable. In addition, the concept of promising zone, as suggested by MP, gives the desired power and smaller average sample size, and thus increases the efficiency of the trial design.