A Cost Effective Approach to the Design and Analysis of Multi–group Experiments

In this communication it is shown that employing statistical methods which account for constraints, inherent in some scientific problems, will often lead to a substantial reduction in the sample size required while simultaneously maintaining the power of the study and its scientific validity. In fact a 40%, or even higher, reduction in the required sample size is possible. These savings have the potential to impact individual labs and researchers and will translate to saving of millions of dollars annually for granting authorities and federal agencies such as the NIH.