STRENGTH OF FACTORS IN 𝟑𝟑 FACTORIAL DESIGNS USING BAYESIAN ANALYSIS

The study proposes to consider factorial design at three levels and identify all significant factors
based on its inherent strength. The methodology considers full, fractional, and reduced factori al designs with three factors each at three levels, to examine the effectiveness of factors in
these models through simulation and employing real data. By identifying and quantifying the
Bayes factors through simulated datasets, the true strength of the main/interaction effects in
these three designs were discovered. Finally, the study concludes that reduced factorial design
produces better results than traditional one-third fractional factorial designs when there are no
other constraints to adding more factors to the model for analysis.