Plackett-Burman design is a statistical experimental design that is used in the field of experimental design. It is a type of factorial design that identifies the main effects of a large number of variables on a response variable quickly and efficiently. When the number of variables is too large to fit into a full factorial design, or when the researcher only wants to identify the most important variables, this design is especially useful. The Plackett-Burman design is a type of fractional factorial design that employs a small number of runs to determine the main effects of variables while controlling for the confounding effects of higher-order interactions. The Plackett-Burman design has the following drawbacks:
Plackett-Burman design has limited power to detect interactions between variables and is not appropriate for detecting higher-order interactions.
No estimation of variable importance: The Plackett-Burman design does not provide an estimation of the relative importance of the variables, which can make prioritising follow-up studies or making decisions based on the results difficult.
Plackett-Burman design does not allow for response variable optimization because it only identifies the main effects of the variables.
Plackett-Burman design requires a limited number of runs and may not be appropriate for experiments that require a large number of runs to achieve sufficient accuracy.
Complexity: The results of a Plackett-Burman design can be difficult to interpret, particularly for experiments with a large number of variables, making it difficult to draw meaningful conclusions.
