Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 98 for “"Multicollinearity"”.
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Spatial variation of the food price index in Canada's Northwest Territories: a ridge regression analysis
… combination of this effect and that of inherent multicollinearity among the variables. For this reason it is felt that at the present stage of the investigation of northern food prices, priority must be given to constructing clear, unambiguous statistical models before further interpretive …
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Early identification of individuals who may fail to reach employment
… has wider application in the identification of multicollinearity within empirical research.
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Projecting new money requests for the Baltimore Federal Intermediate Credit Bank
… new money requests. Due to the presence of multicollinearity, the individual effects of the independent variables are not identified. Multicollinearity was not a concern, however, since the model is to be used exclusively for forecasting. In addition to the statistical results, a …
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A detailed investigation of the linear model and some of its underlying assumptions
… model. In Chapter 2 we deal with the problem of multicollinearity. We investigate the sources of near singularities, we give some methods of detecting the multicollinearity, and we state briefly methods for overcoming this problem. In Chapter 3 we consider the least squares method with …
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Some New Estimator in Linear Mixed Models with Measurement error
… the effect of measurement errors into account. Multicollinearity and fixed-effect variables with measurement errors are two well-known problems in the analysis of linear regression models. Although there exists a large amount of research on these two problems, there is by now no single technique …
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Development and validation of a patient-based outcome measure for endodontic treatment
… care and at one month follow-up visit. Using multicollinearity, factor analysis, regression modelling and an expert based approach items were identified for a brief instrument. The newly developed brief instrument was tested for its reliability, validity and responsiveness on patients …
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Analysis of Precision Agriculture Datasets for on -Farm Research
… limitations due to differential spatial scaling, multicollinearity, and autocorrelation. The main objective of the presented studies is to evaluate methods of analysis for large datasets generated on farm using PA technologies. In order to achieve my objective, I presented two major research …
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Deriving statistical inference from the application of artificial neural networks to clinical metabolomics data
… data are complex with a high degree of multicollinearity. As such, multivariate linear projection methods, such as partial least squares discriminant analysis (PLS-DA) have become standard. Non-linear projections methods, typified by Artificial Neural Networks (ANNs) may be more …
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Does Natural Resource Wealth Spoil and Corrupt Governments? A New Test of the Resource Curse Thesis
… set is used to estimate these models. Due to multicollinearity, only an effect of metals and ores exports on corruption can be discerned. Marginal effects computations show that whether nature corrupts or not crucially depends on a country's institutions. A broad tax base and high levels of …
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Determination of fertility rating (FR) in the 3-PG model for loblolly pine (Pinus taeda L.) plantations in the southeastern United States
… squares methods were found unsuitable due to multicollinearity among the soil variables. In the second approach, a multivariate modeling approach, partial least squares regression, was used to mitigate multicollinearity effects. The best model to quantify soil fertility using soil physical and …
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A comparison of three prediction based methods of choosing the ridge regression parameter k
… least squares. However, when the condition of multicollinearity exists among the regressor variables, then many qualities of this solution deteriorate. The qualities include the variances, the length, the stability, and the prediction capabilities of the solution. An analysis called ridge …
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Development and Demonstration of Surrogate Models to Predict Energy-Related Building Features from Heating and Cooling Load Signature
… in predictions, with clustering addressing multicollinearity, offering a scalable alternative to traditional audits. A user-friendly software tool illustrating the real-world application of the surrogate model is also introduced.
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Pricing methods for American options
… For this approach the impact of outliers and multicollinearity is examined and alternative regression models fitted. Monte Carlo Simulation is implemented to calculate early exercise probabilities of American options in the South African market. Results are compared for both call and put …
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Fractional principal components regression: a general approach to biased estimators
… alternatives to the least squares estimator when multicollinearity is present in the multiple linear regression model. Though the ridge estimator and the principal components estimator have been widely used for such problems, it should be noted that their performances in terms of mean square error …
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The Effect Of Biculturalism On Self-Esteem In Northern Plains Native American College Students
… weak-to-moderate predictors of self-esteem. The multicollinearity of the NPBI subscales requires caution in interpreting this and any other data which utilizes this scale. Recommendations for future research in Biculturalism Measurement and Native American Mental Health are discussed.</p>
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Stressful Work and Turnover: The Mediating Role of Psychological Strain
… in the model. Believing this was due to multicollinearity, I examined a revised model which better fit the data, and supported all nine hypotheses. Furthermore, psychological strain in the form of job dissatisfaction and emotional exhaustion fully mediated the relationship between stress …
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Examining how comfortable Students are in Contacting Campus Police at Central Washington University
… and effectiveness) were analyzed, but due to multicollinearity between these variables, the general attitudes variable was the only one used in the final analysis. The study used four dependent variables, including general matters, personal matters, criminal matters, and safety concerns as the …
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Landsat : water quality surveillance of Roodeplaat Dam
… between chlorophyll a and turbidity and the multicollinearity evident between the four reflectance bands, demanded that a multi-variate statistical technique be implemented, in order to adequately analyse the available data.
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Joint Hedonic Travel Cost Method: Combining Revealed and Stated Preference Data to Estimate Demand for Attribute Quality of Sport Fishing in Illinois
… better quality data to overcome the problem of multicollinearity and appearance of negative implicit prices. The hedonic travel cost models are specified by combining hedonic price functional forms (linear, semilog) and data types (revealed, stated, pooled data). Prior to the estimation of the …
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Empirical Evidence of the Effects of Public Spending on Economic Growth from BRICS
… Defense and Infrastructure. We checked for Multicollinearity using Variance Inflation Factors (VIF's) and used the Hausman Test to determine which statistical model to use. The study followed the fixed effects statistical model. The empirical results support the null hypotheses that health, …
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