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.
Results
Showing 1 to 20 of 24 for “"Significance Testing"”.
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Modern Methods for Variable Significance Testing
… the ubiquitous statistical problem of variable significance testing. The first chapter contains an account of classical approaches to variable significance testing including different perspectives on how to formalise the notion of `variable significance'. The historical development is contrasted …
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The Rise Of Null Hypothesis Significance Testing As The Gold Standard In Psychology, 1940-55
… Nearly every psychologist uses null hypothesis significance testing (NHST) to analyze and draw conclusions from quantitative data, despite its imperfections and the heavy criticisms it has received, particularly in recent years. Though NHST is usually taught as a strictly formalized, “objective” …
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Decision value of confidence intervals versus significance testing in surgical research: a mixed methods study
… this has led to poor clinical decision-making. Significance testing, the conventional statistical approach in medical research, has been suggested to be the leading cause of the misunderstandings. Despite the extensive discussion in the literature, there is limited evidence on whether the …
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The relationships between discrete and continuous probability distributions
… are used for setting confidence limits and significance testing of hypotheses. In Chapter 1, statements of all distributions and mathematical functions used in this thesis are made, and also some approximations are mentioned without proofs. In Chapter 2, exact relationships between discrete …
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A psychophysical investigation of quantum cognition: An interdisciplinary synthesis
… with Fisherian/Neyman-Pearsonian null hypothesis significance testing, we contrasted various alternative statistical approaches which are based on complementary inferential frameworks (i.e., classical null hypothesis significance testing, nonparametric bootstrapping, model comparison based on …
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The relationship between socioeconomic status and competitive sport anxiety in youth
… one hour before competing in sport. Significance testing (t-test) was conducted to determine any difference between affluent and middle class athletes in somatic, cognitive A-state anxiety and self-confidence. The results revealed a lack of statistical difference between the two …
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Addressing the Issue of Meta-Analysis Multiplicity in Education and Psychology
… of multiplicity, conducting multiple statistical significance tests in one study, has pervaded primary research over the last 7 decades (Hochberg & Tamhane, 1987). This continued discussion was due to the fact that multiplicity increases the probability of committing a Type 1 error (i.e., deriving …
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Assessment of Multiple Third-Party Risk Models Incorporating Uncertainty Quantification and Sensitivity Analysis
… the two one-sided tests (TOST), null-hypothesis significance testing, effect size (Hedge's g), and post-hoc power analysis results; which show that QUADRA and AutoPRep produce statistically equivalent expected fatality rates when inputs are aligned, while GRASP exhibits non-equivalent behavior …
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Three Essays on Econometric Analysis
… procedure and the conventional nonparametric significance testing frameworks. In chapter 3, a bootstrap test statistic is proposed to test the validity of imposing some arbitrary restrictions on higher order derivatives of a regression function. We use data sharpening method to enforce the …
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Rapid 3D characterization of whole vertebrate brain at cellular resolution
… correlation analysis, voxel-wise significance testing, and colocalization clustering-are applied to the reconstructed 3D dataset to automatically detect phenotypic changes. The system has been used to screen full brain phenotype at cellular resolution in a well-studied mutant line …
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Pushing the limits of traditional unsupervised learning
… Then two novel methods are provided for testing the significance and reliability of clusters, in which the null-hypothesis statistical distribution is formed either by: (1) a uniform distribution projected onto the principal components of the original data; or (2) a randomized, weighted …
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A hitchhiker’s guide to efficient non-projective dependency parsing
… parsers: inference, sampling, decoding, and significance testing. The thesis will guide the reader through a series of novel extensions to existing algorithms, as well as the original develop- ment of new algorithms concerning these four processes in the dependency parsing galaxy. We provide …
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Neuropsychological and functional magnetic resonance imaging investigations of anterior temporal lobe language function in patients with epilepsy : a pilot study
… The first study employed neuropsychological testing of pre-and post-surgical TLE patients on 3 conventional tests of language function, the Boston Naming Test (BNT), Controlled Oral Word Association Test (COWAT) and Animal Fluency, and one novel test: The Category Specific Names Test (CSNT). …
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Statistical Inference for Diagnostic Classification Models
… development in educational and psychological testing. Instead of an overall test score, a diagnostic test provides each subject with a profile detailing the concepts and skills (often called "attributes") that he/she has mastered. Central to many DCMs is the so-called Q-matrix, an incidence …
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Drought predictions: applications in Australia.
… for forecasting rainfall are compared using significance testing based on multiple comparison techniques. Further to this, rainfall forecasting relationships are explored using global sea-surface temperature anomalies. The versatility of copula models is demonstrated through short-term …
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Evaluating Hybrid Quantum-Classical Models for Image Classification in the NISQ Era
… random seeds per condition and comprehensive significance testing. During the testing with binary datasets, classical methods (SVM, logistic regression, k-NN, neural networks) achieved 85.9% to 99.6% accuracy with training times under one second across all sample sizes. Quantum kernel methods …
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What can we learn from climate data? : Methods for fluctuation, time/scale and phase analysis
… is evaluated by means of error bars and significance testing. On the one hand, such a test should be capable to detect interesting features, i.e. be sensitive. On the other hand, it should be robust and sort out false positive results, i.e. be specific. This thesis mainly aims to …
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Feasibility of an Experiential Community Garden and Nutrition Program for Youth Living in Public Housing:Exploring Outcomes from Youth, Parents and Site Leaders
… implementation, and limited-effectiveness testing) of a 10-week experiential theory-based gardening and nutrition education program targeting youth living in two public housing sites in the Dan River Region. Methods: Using pre- and post-program questionnaires/interviews, demand and …
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Perception and Language: Using the Rorschach with People with Aphasia
… non-fluent aphasia could not be validated with significance testing, descriptive analyses showed some differences in means and standard deviations of Rorschach variable scores between the two groups. Specifically, individuals in the non-fluent aphasia group, who had more impairment in language …
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The Burden of Hepatitis B Among People Living with HIV in East Africa: Evidence from 2016?2019 Population-Based HIV Impact Assessment Surveys
… descriptive measures, logistic regression, and significance testing (P < 0.05). Results: A total of 4,944 PLWH were included in this analysis, of the total 4,944 PLWH screened for HBV 248 (5.02%) were HBV-positive. The median age of PLWH participants was 36.5 years (IQR: 30– 45), while …
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