Optimal experimental design for parameter identification and model selection

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2014

Experimental design for acquiring relevant data to address the issue of comparing consecutively manufactured tools and firearms

The comparison of consecutively manufactured tools and firearms has provided much, but not all, of the basis for the profession of firearm and toolmark examination. The authors accept the fundamental soundness of this approach but appeal to the experimental community to close two minor gaps in the experimental procedure. We suggest that "blinding" and attention to appropriateness of other experimental conditions that would consolidate the foundations of our profession. We do not suggest that previous work is unsound.

Predicting random level and seasonality of hotel prices. A structural equation growth curve approach

This article examines the effect on price of different characteristics of holiday hotels in the sun-and-beach segment, under the hedonic function perspective. Monthly prices of the majority of hotels in the Spanish continental Mediterranean coast are gathered from May to October 1999 from the tour operator catalogues. Hedonic functions are specified as random-effect models and parametrized as structural equation models with two latent variables, a random peak season price and a random width of seasonal fluctuations. Characteristics of the hotel and the region where they are located are used as predictors of both latent variables. Besides hotel category, region, distance to the beach, availability of parking place and room equipment have an effect on peak price and also on seasonality. 3- star hotels have the highest seasonality and hotels located in the southern regions the lowest, which could be explained by a warmer climate in autumn

Simultaneous estimation of indirect and interaction effects using structural equation models

Interaction effects are usually modeled by means of moderated regression analysis. Structural equation models with non-linear constraints make it possible to estimate interaction effects while correcting formeasurement error. From the various specifications, Jöreskog and Yang's(1996, 1998), likely the most parsimonious, has been chosen and further simplified. Up to now, only direct effects have been specified, thus wasting much of the capability of the structural equation approach. This paper presents and discusses an extension of Jöreskog and Yang's specification that can handle direct, indirect and interaction effects simultaneously. The model is illustrated by a study of the effects of an interactive style of use of budgets on both company innovation and performance

Application of the european customer satisfaction index to postal services. Structural equation models versus partial least squars

Customer satisfaction and retention are key issues for organizations in today’s competitive market place. As such, much research and revenue has been invested in developing accurate ways of assessing consumer satisfaction at both the macro (national) and micro (organizational) level, facilitating comparisons in performance both within and between industries. Since the instigation of the national customer satisfaction indices (CSI), partial least squares (PLS) has been used to estimate the CSI models in preference to structural equation models (SEM) because they do not rely on strict assumptions about the data. However, this choice was based upon some misconceptions about the use of SEM’s and does not take into consideration more recent advances in SEM, including estimation methods that are robust to non-normality and missing data. In this paper, both SEM and PLS approaches were compared by evaluating perceptions of the Isle of Man Post Office Products and Customer service using a CSI format. The new robust SEM procedures were found to be advantageous over PLS. Product quality was found to be the only driver of customer satisfaction, while image and satisfaction were the only predictors of loyalty, thus arguing for the specificity of postal services

Experimental design on the simplex

Optimum experimental designs depend on the design criterion, the model andthe design region. The talk will consider the design of experiments for regressionmodels in which there is a single response with the explanatory variables lying ina simplex. One example is experiments on various compositions of glass such asthose considered by Martin, Bursnall, and Stillman (2001).Because of the highly symmetric nature of the simplex, the class of models thatare of interest, typically Scheff´e polynomials (Scheff´e 1958) are rather differentfrom those of standard regression analysis. The optimum designs are also ratherdifferent, inheriting a high degree of symmetry from the models.In the talk I will hope to discuss a variety of modes for such experiments. ThenI will discuss constrained mixture experiments, when not all the simplex is availablefor experimentation. Other important aspects include mixture experimentswith extra non-mixture factors and the blocking of mixture experiments.Much of the material is in Chapter 16 of Atkinson, Donev, and Tobias (2007).If time and my research allows, I would hope to finish with a few comments ondesign when the responses, rather than the explanatory variables, lie in a simplex.ReferencesAtkinson, A. C., A. N. Donev, and R. D. Tobias (2007). Optimum ExperimentalDesigns, with SAS. Oxford: Oxford University Press.Martin, R. J., M. C. Bursnall, and E. C. Stillman (2001). Further results onoptimal and efficient designs for constrained mixture experiments. In A. C.Atkinson, B. Bogacka, and A. Zhigljavsky (Eds.), Optimal Design 2000,pp. 225–239. Dordrecht: Kluwer.Scheff´e, H. (1958). Experiments with mixtures. Journal of the Royal StatisticalSociety, Ser. B 20, 344–360.1

Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling

The interpretation of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all crossloadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores.

Cost-effective experimental design to support modeling of concentration-response functions

Modeling concentration-response function became extremely popular in ecotoxicology during the last decade. Indeed, modeling allows determining the total response pattern of a given substance. However, reliable modeling is consuming in term of data, which is in contradiction with the current trend in ecotoxicology, which aims to reduce, for cost and ethical reasons, the number of data produced during an experiment. It is therefore crucial to determine experimental design in a cost-effective manner. In this paper, we propose to use the theory of locally D-optimal designs to determine the set of concentrations to be tested so that the parameters of the concentration-response function can be estimated with high precision. We illustrated this approach by determining the locally D-optimal designs to estimate the toxicity of the herbicide dinoseb on daphnids and algae. The results show that the number of concentrations to be tested is often equal to the number of parameters and often related to the their meaning, i.e. they are located close to the parameters. Furthermore, the results show that the locally D-optimal design often has the minimal number of support points and is not much sensitive to small changes in nominal values of the parameters. In order to reduce the experimental cost and the use of test organisms, especially in case of long-term studies, reliable nominal values may therefore be fixed based on prior knowledge and literature research instead of on preliminary experiments

Structural Analysis and Overlay Design of Pavements Using the Road Rater, MLR-84-3, 1986

In recent years the Iowa DOT has shifted emphasis from the construction of new roads to the maintenance and preservation of existing highways. A need has developed for analyzing pavements structurally to select the correct rehabilitation strategy and to properly design a pavement overlay if necessary. This need has been fulfilled by Road Rater testing which has been used successfully on all types of pavements to evaluate pavement and subgrade conditions and to design asphaltic concrete overlays. The Iowa Road Rater Design Method has been simplified so that it may be easily understood and used by the widely diverse groups of individuals which may be involved in pavement restoration and management. Road Rater analysis techniques have worked well to date and have been verified by pavement coring, soils sampling and testing, and pavement removal by block sampling. Void detection testing has also been performed experimentally in Iowa, and results indicate that the Road Rater can be used to locate pavement voids and that Road Rater analysis techniques are reasonably accurate. The success of Road Rater research and development has made deflection test data one of the most important pavement management inputs.

Optimisation of the lipase-catalysed preparation of a nucleoside prodrug model using an experimental design methodology

The preparation of 2', 3'-di-O-hexanoyluridine (2) by a Candida antarctica B lipase-catalysed alcoholysis of 2', 3', 5'-tri-O-hexanoyluridine (1) was optimised using an experimental design. At 25 ºC better experimental conditions allowed an increase in the yield of 2 from 80% to 96%. In addition to the yield improvement, the volume reaction could be diminished in a factor of 5 and the reaction time significantly shortened.

Nanoparticle-coated organic-inorganic microparticles: experimental design and gastrointestinal tolerance evaluation

The influences of the spray-drying parameters and the type of nanoparticles (nanocapsules or nanospheres) on the characteristics of nanoparticle-coated diclofenac-loaded microparticles were investigated by using a factorial design 3². Gastrointestinal tolerance following oral administration in rats was evaluated. Formulations were selected considering the best yields, the best encapsulation efficiencies and the lowest water contents, presenting surfaces completely coated by nanostructures and a decrease in the surface areas in relation to the uncoated core. In vitro drug release demonstrated the influence of the nanoparticle-coating on the dissolution profiles of diclofenac. Nanocapsule-coated microparticles presented a protective effect on the gastrointestinal mucosa.

Gemifloxacin mesylate: UV spectrophotometric method for quantitative determination using experimental design for robustness

This study describes the validation of UV spectrophotometric method for quantitative determination of gemifloxacin mesylate (GFM) in tablets using methanol as solvent. The method was specific, linear, precise, exact and robust at 272 and 343 nm. The results confirmed that the method in both wavelengths is valid and useful to the routine quality control of GFM in coated tablets. The validate method was compared to liquid chromatography (HPLC), microbiological assay and visible (VIS) spectrophotometry, which were previously developed and validated to the same drug. There was not significative difference between the methods for GFM quantitation.

Use of experimental design in the optimisation of a solid phase preconcentration system for Cobalt determination by GFAAS

In this work is proposed a solid phase preconcentration system of Co2+ ions and its posterior determination by GFAAS in which fractional factorial design and response surface methodology (RSM) were used for optimization of the variables associated with preconcentration system performance. The method is based on cobalt extraction as a complex Co2+-PAN (1:2) in a mini-column of polyurethane foam (PUF) impregnated with 1-(2-pyridylazo)-naphthol (PAN) followed by elution with HCl solution and its determination by GFAAS. The chemical and flow variables studied were pH, buffer concentration, eluent concentration and preconcentration and elution flow rates. Results obtained from fractional factorial design 2(5-1) showed that only the variables pH, buffer concentration and interaction (pH X buffer concentration) based on analysis of variance (ANOVA) were statistically significant at 95% confidence level. Under optimised conditions, the method provided an enrichment factor of 11.6 fold with limit of detection and quantification of 38 and 130 ng L-1, respectively, and linear range varying from 0.13 to 10 µg L-1. The precision (n = 9) assessed by relative standard deviation (RSD) was respectively 5.18 and 2.87% for 0.3 and 3.0 µg L-1 cobalt concentrations.