Date Added: Mar 2010
A proper experimental design is important to ensure that data collected in a study is relevant to answer research questions. However, a predefined, textbook classical design rarely provides an exact match to real-world research problems. There are usually unique restrictions and constraints involved in the whole experimentation process. Fortunately, with the advancement of computing power and SAS software development, users can generate custom designs based on optimal algorithms. This paper presents a flexible approach using JMP Design of Experiments (DOE) designer in conjunction with the SAS OPTEX procedure to create optimal experiments that are tailored to the specific needs.