Application of statistical experimental design

Application of Statistical Experimental Design to Development of Low-Density Polymer Foams... 

This chapter will examine the application of statistical experimental design to designing a product or process that is robust to variation from environmental variables. It should be understood that the phrase environmental variables is to be viewed broadly and is not just limited to variables such as temperature and humidity. In this context, variation from environmental variables is variation that is external to the product and that is outside of the control of the manufacturer during production. Thus, it might also include variation in the conditions in which the customer uses the product, or in the conditions in which the product is stored, or in how the product is maintained and serviced. 

Sjostrom, M. and Eriksson, L. Application of Statistical Experimental Design and PLS Modelling in QSAR. In QSAR Chemometric Methods in Molecular Design, Methods and Principles in Medicinal Chemistry, 2, Ed. H. van de Waterbeemd. Verlag Chemie, Weinheim, Germany, 1995... 

Fangmark I (1993), Formation of chlorinated aromatic compounds during incineration - an application of statistical experimental design", Dissertation, Universitat Ume3, Schweden Griffin RD (1987), Chemosphere 15 1987-1990. A new theory of dioxin formation in municipal solid waste combustion"... 

For our validations, a CVp is a pooled estimate calculated from the particular type of statistical data set (36 samples) described earlier in the Statistical Experimental Design section of this report. A statistical procedure is given in Hald JL for determining an upper confidence limit for the coefficient of variation. This general theory had o be adapted appropriately for application to a pooled CVp estimate. For this design, and under the stated assumptions, there is a one-to-one correspondence between values of CVp and upper confidence limits for CVp. Therefore, the confidence limit criterion given above is equivalent to another criterion based on the relationship of CVp and its critical value. The... 

As drug development became of greater importance during the first half of the twentieth century, a more quantitative and analytical foundation was needed to assess drug potency per se as well as comparative drug potency. The standardization and quantification of technique and experimental design, and the rigorous application of statistical analysis, have provided pharmacodynamics with a necessary solid base. 

It first introduces the reader to the fundamentals of experimental design. Systems theory, response surface concepts, and basic statistics serve as a basis for the further development of matrix least squares and hypothesis testing. The effects of different experimental designs and different models on the variance-covariance matrix and on the analysis of variance (ANOVA) are extensively discussed. Applications and advanced topics such as confidence bands, rotatability, and confounding complete the text. Numerous worked examples are presented. 

Statistical experimental design, also called design of experiments (DoE), is a well-established concept for planning and execution of informative experiments. DoE can be used in many applications. An important type of DoE application refers to the preparation and modification of mixtures. It involves the use of mixture designs for changing mixture composition and exploring how such changes will affect the properties of the mixture [32],... 

Examples of applications of statistical designs for optimising correlations with in vivo data and for the testing of a formulation under different experimental conditions to elucidate the sensitivity of the drug release towards different physiological factors have also been published (Abrahamsson et al. 1999 Abuzarur-Aloul et al. 1997). 

Experimental design and performance analysis of alumina coatings deposited by a detonation spray process Adjustment of the band gap energies of biostabilized CdS nanoparticles by application of statistical DoE Experimental design and optimization of dispersion process for single-walled carbon nanotube bucky paper... 

The robustness of an RP-HPLC method can generally be established in two different ways, either during a systematic method development [1, 6,10,11] or by the application of a statistical experimental design [2-5,13, 15-36]. 

The application of statistical methods depends on a proper experimental design, for the training set from which a QSAR model is derived, as well as for the test set, for which biological data shall be predicted (e.g.. Refs. 4,5, 10). In QSAR analyses, this important precondition is most often neglected. No wonder that in such cases problems arise from a biased object selection and from different structural and parameter spaces of the training and test sets. 

---