Sample size calculations: basic principles and common pitfalls

Abstract

Nephrol Dial Transplant 2010; doi:10.1093/ndt/gfp732 The publisher regrets that this article was published with the following errors: 2 rules in Table 1 are missing. The table should have been displayed as follows: In Box 1 the line in the formula is too long. The formula should have been displayed as follows: Box 1: Simplest formula for a continuous outcome and equal sample sizes in both groups, assuming: alpha = 0.05 and power = 0.80 (beta = 0.20). Box 1: Simplest formula for a continuous outcome and equal sample sizes in both groups, assuming: alpha = 0.05 and power = 0.80 (beta = 0.20). n = the sample size in each of the groups μ1 = population mean in treatment Group 1 μ2 = population mean in treatment Group 2 μ1 − μ2 = the difference the investigator wishes to detect σ2 = population variance (SD) a = conventional multiplier for alpha = 0.05 Finally, in box 2 the word “subjects” is missing. This should have read:Box 2: Simplest formula for a binary outcome and equal sample sizes in both groups, assuming: alpha = 0.05 and power = 0.80 (beta=0.20). n = the sample size in each of the groups p1 = proportion of subjects with hypertension in treatment Group 1 q1 = proportion of subjects without hypertension in treatment Group 1 (= 1− p1) p2 = proportion of with hypertension in treatment Group 2 q2 = proportion of subjects without hypertension in treatment Group 2 (= 1− p2) x = the difference the investigator wishes to detect a = conventional multiplier for alpha = 0.05 b = conventional multiplier for power = 0.80