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 1396 for “"Regression Model"”.
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Outliers in a Linear Regression Model
Over the last several decades the linear regression model has become one of the most widely used tools of the social sciences and the physical sciences. Given the data, the least squares method gives information for statistical inferences. However, the researcher frequently feels that the …
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The development of the LIM regression model
Not available
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Unified Ordinal Regression: Model Assessment and Semiparametric Analysis
… least squares algorithm for cumulative link models for ordinal responses.
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Optimal designs for a bivariate logistic regression model
… interest are efficacy and toxicity. These can be modeled as a bivariate quantal response using the Gumbel model for bivariate logistic regression. D-optimal and Q-optimal experimental designs are developed for this model The Q-optimal design minimizes the average asymptotic prediction variance of …
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Power analysis for a mixed effects logistic regression model
… herd health studies, the mixed effects logistic regression model with random herd effects are commonly used for modeling clustered binary data. These models are well developed and widely used in the literature, among which is the logistic-normal regression model. In contrast to the rich …
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A poisson regression model for assessing force majeure claims
Empirical legal analysis is an emerging discipline of statistical and legal scholarship. Despite its importance, however, there is a lack of empirical research on the affirmative defense of force majeure, which eliminates liability for a breach of contract in the case of an unforeseeable and …
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Berkson's method vs. maximum likelihood in the logistic regression model
Call number: LD2668 .R4 STAT 1988 R33
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Berkson's method vs. maximum likelihood in the logistic regression model
Call number: LD2668 .R4 STAT 1988 R33
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Application of ordered latent class regression model in educational assessment
… Croon (1990) proposed the ordered latent class model where latent classes are ordered by imposing inequality constraints on the cumulative conditional response probabilities. Taking stochastic ordering of latent classes into account in the analysis of data gives a meaningful interpretation, …
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Optimal Experimental Designs for the Poisson Regression Model in Toxicity Studies
… experimental designs for generalized linear models have received increasing attention in recent years. Yet, most of the current research focuses on binary data models especially the one-variable first-order logistic regression model. This research extends this topic to count data models. The …
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Optimal one and two-stage designs for the logistic regression model
Binary response data is often modeled using the logistic regression model, a well known nonlinear model. Designing an optimal experiment for this nonlinear situation poses some problems not encountered with a linear model. The application of several optimality design criteria to the logistic …
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On testing the change-point in the longitudinal bent line quantile regression model
… sequence into groups, which follow different models. This dissertation considers the change-point problem in quantile regression for observational or clinical studies involving correlated data (e.g. longitudinal studies) . Our research is motivated by the lack of ideal inference procedures for …
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Evaluating Sources of Arsenic in Groundwater in Virginia using a Logistic Regression Model
For this study, I have constructed a logistic regression model, using existing datasets of environmental parameters to predict the probability of As concentrations above 5 parts per billion (ppb) in Virginia groundwater and to evaluate if geologic or other characteristics are linked to elevated As …
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Linear regression model for continuous non-invasive blood pressure estimation for an ICU setting
… a novel, continuous non-invasive BP estimation model with age, gender and heart rate as covariates along with PTT to estimate ICU patient invasive BP data is presented in this pilot-study. The proposed novel model is tested for four common ICU clinical conditions. The results indicate compliance …
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An Accurate VO2max Non-exercise Regression Model for 18 to 65 Year Old Adults
<p>The purpose of this study was to develop a regression equation to predict VO2max based on non-exercise (N-EX) data. All participants (N = 100), aged 18-65 years old, successfully completed a maximal graded exercise test (GXT) to assess VO2max (mean ± SD; 39.96 mL∙kg-¹∙min&sup-1; ± 9.54 …
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Hierarchical regression model tree for explainable actor segmentation and response prediction on social networks
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-04-12 without embargo terms
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Improvisation of fuzzy c-means method and fuzzy linear regression model in predicting manufacturing income
Certain statistical systems for modelling are influenced by human perception. Analysis by human perception could not be solved using traditional method since uncertainty within the data have to be dealt with. Thus, fuzzy structure system is considered. The objectives of this study were to: …
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Quantitative Analysis of Applying Random Coefficient Regression Model to the Short-Run Fluctuations for Hogs
Made available in DSpace on 2014-12-10T22:03:11Z (GMT). No. of bitstreams: 1 7405659.pdf: 5584871 bytes, checksum: c2622a9183e42471ba804e139ea16b07 (MD5) Previous issue date: 1973
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A Zone-Based Multiple Regression Model to Visualize GPS Locations on a Surveillance Camera Image
… happening. My research uses multiple curvilinear regression models to accurately place differentially corrected GPS points with submeter accuracy onto a camera image. Optimal results were achieved after splitting the image into four zones with the focus on calibrating each area separately. This …
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