In designs where there are multiple factors, all with a discrete group of level settings, the full enumeration of all combinations of factor levels is referred to as a full factorial design. As the number of factors increases, potentially along with the settings for the factors, the total number of experimental units increases rapidly. Read the rest of this entry »
Design of Experiments – Full Factorial Designs
December 1st, 2009Design of Experiments – Power Calculations
November 18th, 2009Prior to conducting an experiment researchers will often undertake power calculations to determine the sample size required in their work to detect a meaningful scientific effect with sufficient power. In R there are functions to calculate either a minimum sample size for a specific power for a test or the power of a test for a fixed sample size. Read the rest of this entry »
