Fitting response surface models is usually carried out using statistical packages to solve complicated equations in order to produce the estimates of the model coefficients. This paper proposes a new procedure for fitting response surface models to mixed two-level and four-level factorial designs. New and easier formulae are suggested to calculate the linear, quadratic and the interaction coeff...

A Two-Level Fractional Factorial design was employed to develop and optimize the combination of demographic characteristics that has the greatest effect on the spread of HIV in the South African population. HIV prevalence (dependent variable) was found to be highly sensitive to changes in the mother’s age (15-55years) and level of education (Grades 0-13) (independent variables), using the 2006 ...

Three-factor interaction for the two-level, three-level, and four-level factorial designs was studied. A new technique and formula based on the coefficients of orthogonal polynomial contrast were proposed to calculate the effect of the three-factor interaction The results show that the proposed technique was in agreement with the least squares method. The advantages of the new technique are 1) ...

Herpes simplex virus type 1 (HSV-1) is known to cause diseases of various severities. There is increasing interest to find drug combinations to treat HSV-1 by reducing drug resistance and cytotoxicity. Drug combinations offer potentially higher efficacy and lower individual drug dosage. In this paper, we report a new application of fractional factorial designs to investigate a biological system...

Minimum aberration designs are obtained for two types of mixed-level fractional factorial: (i) (s) × s factorial, and (ii) (s1) × (s2) × s factorial, where s is any prime or prime power, and r, r1, r2 and n are positive integers. Projective geometric tools are employed to find the wordlength pattern of a given design in terms of that of its complementary set. Many useful designs are found

When several treatments are available for evaluation in a clinical trial, different design options are available. We compare multi-arm multi-stage with factorial designs, and in particular, we will consider a 2 × 2 factorial design, where groups of patients will either take treatments A, B, both or neither. We investigate the performance and characteristics of both types of designs under differ...