Abstract
Mixed-level designs are widely used in the practical experiments. When the levels of some factors are difficult to be changed or controlled, fractional factorial split-plot (FFSP) designs are often used. This paper investigates the sufficient and necessary conditions for a \({2^{(n_{1}+n_{2})-(k_1+k_2)}4_s^{1}}\) FFSP design with resolution III or IV to have various clear factorial effects, including two types of main effects and three types of two-factor interaction components. The structures of such designs are shown and illustrated with examples.
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References
Addelman S (1962) Orthogonal main-effect plans for asymmetrical factorial experiments. Technometrics 4: 21–46
Box GEP, Jones S (1992) Split-plot designs for robust product experimentation. J Appl Stat 19: 3–26
Chen H, Hedayat AS (1998) 2n–m designs with resolution III and IV containing clear two-factor interactions. J Stat Plann Inference 75: 147–158
Wu CFJ (1989) Construction of 2m4n designs via a grouping scheme. Ann Stat 17: 1880–1885
Wu CFJ, Chen Y (1992) A graph-aided method for planning two-level experiments when certain interactions are important. Technometrics 34: 162–175
Yang JF, Li PF, Liu MQ, Zhang RC (2006) \({2^{(n_1+n_2)-(k_1+k_2)}}\) fractional factorial split-plot designs containing clear effects. J Stat Plann Inference 136: 4450–4458
Zhao SL, Zhang RC (2008) 2m4n designs with resolution III or IV containing clear two-factor interaction components. Stat Papers 49(3): 441–454
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Zhao, S., Chen, X. Mixed-level fractional factorial split-plot designs containing clear effects. Metrika 75, 953–962 (2012). https://doi.org/10.1007/s00184-011-0361-9
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DOI: https://doi.org/10.1007/s00184-011-0361-9