16 resultados para Statistical experimental design

em Aston University Research Archive


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Competition between three foliose, saxicolous lichens common on slate rock in South Gwynedd, Wales, U.K. was studied experimentally using the de Wit design. Fragments of the three species were cut from the edges of large thalli, glued to 5 x 5 cm plots marked out on pieces of slate which were then placed on boards in the field. For each combination of pairs of species, the two species were grown either in monoculture at a density of 24 fragments per plot or together in three mixtures in differing proportions, i.e. species A:B with 16:8, 12:12 and 8:16 fragments per plot; the density remaining constant throughout. Area of the species in the plots after 3 years was used as an estimate of growth. Physcia orbicularis and Parmelia glabratula ssp. fuliginosa grew similarly in monoculture. In mixtures of the two, growth of each species was linearly related to its proportion in a mixture, suggesting little competition had occurred during three years. By contrast, the growth of Parmelia conspersa in monoculture was significantly greater than that of P. orbicularis or P. glabratula. In addition, the growth of both species was substantially reduced in mixtures with P. conspersa; P. glabratula being eliminated in the mixture in which it was the minority species. These results suggest that P. conspersa should predominate in communities with either of the other two species and, in the absence of P. conspersa, communities dominated by P.orbicularis and P. glabratula should be more stable.

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Competition between three foliose lichens common on slate rock in south Gwynedd, Wales was studied in the field using a factorial experimental design. The lichens were grown as fragments glued to pieces of slate in two- and three-species mixtures. In the two-species mixtures, Parmelia conspersa (Ehrh. Ex Ach.) Ach. outcompeted Parmelia glabratula ssp. fuliginosa (Fr. ex Duby) Laund. strongly and Physcia orbicularis (Neck.) Poetsch less strongly, while P. orbicularis outcompeted P. glabratula weakly. Significant two-factor interactions indicated that the results from the three-species mixture could not be predicted from the two-species mixtures. Parmelia glabratula and P. orbicularis grew better in the presence of two competitors than one. This result suggests that the three species may co-occur on well-lit rock surfaces at the site.

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This paper presents a greedy Bayesian experimental design criterion for heteroscedastic Gaussian process models. The criterion is based on the Fisher information and is optimal in the sense of minimizing parameter uncertainty for likelihood based estimators. We demonstrate the validity of the criterion under different noise regimes and present experimental results from a rabies simulator to demonstrate the effectiveness of the resulting approximately optimal designs.

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The key to the correct application of ANOVA is careful experimental design and matching the correct analysis to that design. The following points should therefore, be considered before designing any experiment: 1. In a single factor design, ensure that the factor is identified as a 'fixed' or 'random effect' factor. 2. In more complex designs, with more than one factor, there may be a mixture of fixed and random effect factors present, so ensure that each factor is clearly identified. 3. Where replicates can be grouped or blocked, the advantages of a randomised blocks design should be considered. There should be evidence, however, that blocking can sufficiently reduce the error variation to counter the loss of DF compared with a randomised design. 4. Where different treatments are applied sequentially to a patient, the advantages of a three-way design in which the different orders of the treatments are included as an 'effect' should be considered. 5. Combining different factors to make a more efficient experiment and to measure possible factor interactions should always be considered. 6. The effect of 'internal replication' should be taken into account in a factorial design in deciding the number of replications to be used. Where possible, each error term of the ANOVA should have at least 15 DF. 7. Consider carefully whether a particular factorial design can be considered to be a split-plot or a repeated measures design. If such a design is appropriate, consider how to continue the analysis bearing in mind the problem of using post hoc tests in this situation.

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Background: Emotional eating in children has been related to the consumption of energy-dense foods and obesity, but the development of emotional eating in young children is poorly understood. Objectives: We evaluated whether emotional eating can be induced in 5-7-y-old children in the laboratory and assessed whether parental use of overly controlling feeding practices at 3-5 y of age predicts a greater subsequent tendency for children to eat under conditions of mild stress at ages 5-7 y. Design: Forty-one parent-child dyads were recruited to participate in this longitudinal study, which involved parents and children being observed consuming a standard lunch, completing questionnaire measures of parental feeding practices, participating in a research procedure to induce child emotion (or a control procedure), and observing children's consumption of snack foods. Results: Children at ages 5-7 y who were exposed to a mild emotional stressor consumed significantly more calories from snack foods in the absence of hunger than did children in a control group. Parents who reported the use of more food as a reward and restriction of food for health reasons with their children at ages 3-5 y were more likely to have children who ate more under conditions of negative emotion at ages 5-7 y. Conclusions: Parents who overly control children's food intake may unintentionally teach children to rely on palatable foods to cope with negative emotions. Additional research is needed to evaluate the implications of these findings for children's food intake and weight outside of the laboratory setting. This trial was registered at clinicaltrials.gov as NCT01122290.

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Plasma or "dry" etching is an essential process for the production of modern microelectronic circuits. However, despite intensive research, many aspects of the etch process are not fully understood. The results of studies of the plasma etching of Si and Si02 in fluorine-containing discharges, and the complementary technique of plasma polymerisation are presented in this thesis. Optical emission spectroscopy with argon actinometry was used as the principle plasma diagnostic. Statistical experimental design was used to model and compare Si and Si02 etch rates in CF4 and SF6 discharges as a function of flow, pressure and power. Etch mechanisms m both systems, including the potential reduction of Si etch rates in CF4 due to fluorocarbon polymer formation, are discussed. Si etch rates in CF4 /SF6 mixtures were successfully accounted for by the models produced. Si etch rates in CF4/C2F6 and CHF3 as a function of the addition of oxygen-containing additives (02, N20 and CO2) are shown to be consistent with a simple competition between F, 0 and CFx species for Si surface sites. For the range of conditions studied, Si02 etch rates were not dependent on F-atom concentration, but the presence of fluorine was essential in order to achieve significant etch rates. The influence of a wide range of electrode materials on the etch rate of Si and Si02 in CF4 and CF4 /02 plasmas was studied. It was found that the Si etch rate in a CF4 plasma was considerably enhanced, relative to an anodised aluminium electrode, in the presence of soda glass or sodium or potassium "doped" quartz. The effect was even more pronounced in a CF4 /02 discharge. In the latter system lead and copper electrodes also enhanced the Si etch rate. These results could not be accounted for by a corresponding rise in atomic fluorine concentration. Three possible etch enhancement mechanisms are discussed. Fluorocarbon polymer deposition was studied, both because of its relevance to etch mechanisms and its intrinsic interest, as a function of fluorocarbon source gas (CF4, C2F6, C3F8 and CHF3), process time, RF power and percentage hydrogen addition. Gas phase concentrations of F, H and CF2 were measured by optical emission spectroscopy, and the resultant polymer structure determined by X-ray photoelectron spectroscopy and infrared spectroscopy. Thermal and electrical properties were measured also. Hydrogen additions are shown to have a dominant role in determining deposition rate and polymer composition. A qualitative description of the polymer growth mechanism is presented which accounts for both changes in growth rate and structure, and leads to an empirical deposition rate model.

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Analysis of variance (ANOVA) is the most efficient method available for the analysis of experimental data. Analysis of variance is a method of considerable complexity and subtlety, with many different variations, each of which applies in a particular experimental context. Hence, it is possible to apply the wrong type of ANOVA to data and, therefore, to draw an erroneous conclusion from an experiment. This article reviews the types of ANOVA most likely to arise in clinical experiments in optometry including the one-way ANOVA ('fixed' and 'random effect' models), two-way ANOVA in randomised blocks, three-way ANOVA, and factorial experimental designs (including the varieties known as 'split-plot' and 'repeated measures'). For each ANOVA, the appropriate experimental design is described, a statistical model is formulated, and the advantages and limitations of each type of design discussed. In addition, the problems of non-conformity to the statistical model and determination of the number of replications are considered. © 2002 The College of Optometrists.

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Optimal design for parameter estimation in Gaussian process regression models with input-dependent noise is examined. The motivation stems from the area of computer experiments, where computationally demanding simulators are approximated using Gaussian process emulators to act as statistical surrogates. In the case of stochastic simulators, which produce a random output for a given set of model inputs, repeated evaluations are useful, supporting the use of replicate observations in the experimental design. The findings are also applicable to the wider context of experimental design for Gaussian process regression and kriging. Designs are proposed with the aim of minimising the variance of the Gaussian process parameter estimates. A heteroscedastic Gaussian process model is presented which allows for an experimental design technique based on an extension of Fisher information to heteroscedastic models. It is empirically shown that the error of the approximation of the parameter variance by the inverse of the Fisher information is reduced as the number of replicated points is increased. Through a series of simulation experiments on both synthetic data and a systems biology stochastic simulator, optimal designs with replicate observations are shown to outperform space-filling designs both with and without replicate observations. Guidance is provided on best practice for optimal experimental design for stochastic response models. © 2013 Elsevier Inc. All rights reserved.

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Surface modification by means of nanostructures is of interest to enhance boiling heat transfer in various applications including the organic Rankine cycle (ORC). With the goal of obtaining rough and dense aluminum oxide (Al2O3) nanofilms, the optimal combination of process parameters for electrophoretic deposition (EPD) based on the uniform design (UD) method is explored in this paper. The detailed procedures for the EPD process and UD method are presented. Four main influencing conditions controlling the EPD process were identified as nanofluid concentration, deposition time, applied voltage and suspension pH. A series of tests were carried out based on the UD experimental design. A regression model and statistical analysis were applied to the results. Sensitivity analyses of the effect of the four main parameters on the roughness and deposited mass of Al2O3 films were also carried out. The results showed that Al2O3 nanofilms were deposited compactly and uniformly on the substrate. Within the range of the experiments, the preferred combination of process parameters was determined to be nanofluid concentration of 2 wt.%, deposition time of 15 min, applied voltage of 23 V and suspension pH of 3, yielding roughness and deposited mass of 520.9 nm and 161.6 × 10− 4 g/cm2, respectively. A verification experiment was carried out at these conditions and gave values of roughness and deposited mass within 8% error of the expected ones as determined from the UD approach. It is concluded that uniform design is useful for the optimization of electrophoretic deposition requiring only 7 tests compared to 49 using the orthogonal design method.

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Computer models, or simulators, are widely used in a range of scientific fields to aid understanding of the processes involved and make predictions. Such simulators are often computationally demanding and are thus not amenable to statistical analysis. Emulators provide a statistical approximation, or surrogate, for the simulators accounting for the additional approximation uncertainty. This thesis develops a novel sequential screening method to reduce the set of simulator variables considered during emulation. This screening method is shown to require fewer simulator evaluations than existing approaches. Utilising the lower dimensional active variable set simplifies subsequent emulation analysis. For random output, or stochastic, simulators the output dispersion, and thus variance, is typically a function of the inputs. This work extends the emulator framework to account for such heteroscedasticity by constructing two new heteroscedastic Gaussian process representations and proposes an experimental design technique to optimally learn the model parameters. The design criterion is an extension of Fisher information to heteroscedastic variance models. Replicated observations are efficiently handled in both the design and model inference stages. Through a series of simulation experiments on both synthetic and real world simulators, the emulators inferred on optimal designs with replicated observations are shown to outperform equivalent models inferred on space-filling replicate-free designs in terms of both model parameter uncertainty and predictive variance.

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In this paper we present a novel method for emulating a stochastic, or random output, computer model and show its application to a complex rabies model. The method is evaluated both in terms of accuracy and computational efficiency on synthetic data and the rabies model. We address the issue of experimental design and provide empirical evidence on the effectiveness of utilizing replicate model evaluations compared to a space-filling design. We employ the Mahalanobis error measure to validate the heteroscedastic Gaussian process based emulator predictions for both the mean and (co)variance. The emulator allows efficient screening to identify important model inputs and better understanding of the complex behaviour of the rabies model.

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This thesis has two aims. First, it sets out to develop an alternative methodology for the investigation of risk homeostasis theory (RHT). It is argued that the current methodologies of the pseudo-experimental design and post hoc analysis of road-traffic accident data both have their limitations, and that the newer 'game' type simulation exercises are also, but for different reasons, incapable of testing RHT predictions. The alternative methodology described here is based on the simulation of physical risk with intrinsic reward rather than a 'points pay-off'. The second aim of the thesis is to examine a number of predictions made by RHT through the use of this alternative methodology. Since the pseudo-experimental design and post hoc analysis of road-traffic data are both ill-suited to the investigation of that part of RHT which deals with the role of utility in determining risk-taking behaviour in response to a change in environmental risk, and since the concept of utility is critical to RHT, the methodology reported here is applied to the specific investigation of utility. Attention too is given to the question of which behavioural pathways carry the homeostasis effect, and whether those pathways are 'local' to the nature of the change in environmental risk. It is suggested that investigating RHT through this new methodology holds a number of advantages and should be developed further in an attempt to answer the RHT question. It is suggested too that the methodology allows RHT to be seen in a psychological context, rather than the statistical context that has so far characterised its investigation. The experimental findings reported here are in support of hypotheses derived from RHT and would therefore seem to argue for the importance of the individual and collective target level of risk, as opposed to the level of environmental risk, as the major determinant of accident loss.

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Aims: To assess the effectiveness of a digital-story intervention (short videos made by young people) seeking to reduce the prevalence of young people's binge drinking in Caerphilly. Method: A quasi-experimental design was adopted with three intervention sites and one control site providing the sample (mainly aged 1415 years). Three rounds of self-completion questionnaires, completed prior (T1), immediately after (T2) and 6 months after the intervention (T3). Findings: A total of 1031 questionnaires completed across the three time-points. Two-factor ANOVAs revealed a positive effect on knowledge for the intervention sample. The intervention group results showed stable attitudes towards drinking at the three time-points whilst the control group showed increasing positive attitudes towards drunkenness over the same time period. Intentions towards drunkenness were higher in the control group than the intervention group at T2 (ControlT1 Mean 3.37, T2 Mean 3.90; interventionT1 Mean 3.26, T2 Mean 3.29). Intervention participants got drunk on fewer occasions in the last week (mean occasions last week 1.57) compared to control participants (mean occasions last week 2.00), with the difference approaching statistical significance (F 1.90, p 0.07). Conclusions: Promoting negative attitudes towards drunkenness, alongside a greater sense of control and potential regret about drunkenness are likely to be important factors when considering how to change people's intentions to drink. The study shows the potential to reduce the frequency of drinking behaviour when intentions are changed, and provides recommendations for future interventions of this nature. © 2010 Informa UK Ltd.

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Background - The literature is not univocal about the effects of Peer Review (PR) within the context of constructivist learning. Due to the predominant focus on using PR as an assessment tool, rather than a constructivist learning activity, and because most studies implicitly assume that the benefits of PR are limited to the reviewee, little is known about the effects upon students who are required to review their peers. Much of the theoretical debate in the literature is focused on explaining how and why constructivist learning is beneficial. At the same time these discussions are marked by an underlying presupposition of a causal relationship between reviewing and deep learning. Objectives - The purpose of the study is to investigate whether the writing of PR feedback causes students to benefit in terms of: perceived utility about statistics, actual use of statistics, better understanding of statistical concepts and associated methods, changed attitudes towards market risks, and outcomes of decisions that were made. Methods - We conducted a randomized experiment, assigning students randomly to receive PR or non–PR treatments and used two cohorts with a different time span. The paper discusses the experimental design and all the software components that we used to support the learning process: Reproducible Computing technology which allows students to reproduce or re–use statistical results from peers, Collaborative PR, and an AI–enhanced Stock Market Engine. Results - The results establish that the writing of PR feedback messages causes students to experience benefits in terms of Behavior, Non–Rote Learning, and Attitudes, provided the sequence of PR activities are maintained for a period that is sufficiently long.

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Analysis of covariance (ANCOVA) is a useful method of ‘error control’, i.e., it can reduce the size of the error variance in an experimental or observational study. An initial measure obtained before the experiment, which is closely related to the final measurement, is used to adjust the final measurements, thus reducing the error variance. When this method is used to reduce the error term, the X variable must not itself be affected by the experimental treatments, because part of the treatment effect would then also be removed. Hence, the method can only be safely used when X is measured before an experiment. A further limitation of the analysis is that only the linear effect of Y on X is being removed and it is possible that Y could be a curvilinear function of X. A question often raised is whether ANCOVA should be used routinely in experiments rather than a randomized blocks or split-plot design, which may also reduce the error variance. The answer to this question depends on the relative precision of the difference methods with reference to each scenario. Considerable judgment is often required to select the best experimental design and statistical help should be sought at an early stage of an investigation.