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 132 for “"Categorical data"”.
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Sequential analysis of categorical data
… have been developed for sequential analysis of categorical data group-wise. These procedures' enables (i) a simple hypothesis to be used for the alternative hypothesis instead of the composite hypothesis commonly used in goodness-of-fit tests, contingency tables, and Mood's non-parametric …
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Empirical analyses of dynamic categorical data
… couples' retirement decision using the PSID data. I employ the proportional hazard model to examine the factors that influence the retirement decision of husband and wife, and focus on examining the correlation of husband and wife's retirement status. This essay finds that an individual is …
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Treemaps: Visualizing Hierarchical and Categorical Data
… method for the visualization of hierarchical and categorical data sets. Treemap presentations of data shift mental workload from the cognitive to the perceptual systems, taking advantage of the human visual processing system to increase the bandwidth of the human-computer interface. Efficient use …
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Bayesian model determination for categorical data survey
Inference for survey data needs to take account of the survey design. Failing to consider the survey design in inference may lead to misleading results. The standard analysis of categorical data, developed under the assumption of multinomial sampling, is inadequate as the commonly used sampling …
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Students’ interpretations of categorical data using dynamic graphical representations
… skill level, ability to interpret bivariate categorical graphs (particularly segmented bar graphs and two-way binned plots), and ability to identify association of two categorical variables were all investigated through interview tasks and responses to inquiry. Students were found to have …
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An investigation into statistical methods for analysing ordered categorical data.
… statistical methods for analysing ordered categorical data. Some standard descriptive and modelling procedures are described, and the data is analysed using a relatively new statistical package, CHAID, which is designed purely for categorical data analysis. The study is centered around the …
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Intelligible models for learning categorical data via generalized fourier spectrum
… This thesis considers learning problems on categorical data and proposes methods that retain the good interpretability of linear models but significantly improve the predictive performance. In particular, we provide ways to automatically generate and efficiently select new features based on …
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The Analysis of Multivariate, Longitudinal Categorical Data by Log-Multilinear Models
… present in 3-mode, multivariate, longitudinal categorical data. They are extensions of loglinear models that provide graphical representations of interactions or associations among discrete variables. The models are generalizations of association models for 2-way tables and are similar to …
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The robustness of LISREL estimates in structural equation models with categorical data
… structural parameter estimates for models with categorical manifest variables. Two types of correlation matrices were analyzed; one containing Pearson product-moment correlations and one containing tetrachoric, polyserial, and product-moment correlations as appropriate. Using continuous …
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Visualising categorical data: Linguistic case studies from te Reo Māori and New Zealand English
Categorical variables are prevalent in real-world datasets across numerous domains, yet few visualisation techniques accommodate them effectively. This is especially true of datasets comprising three or more categorical variables, termed multivariate categorical data. Visualising such data is …
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Models and Graphics in the Analysis of Categorical Variables: The Case of the Youth Tobacco Survey.
… which are of relative recent appearance in categorical data analysis, will be examined, including logistic and log-linear modeling as well as graphical displays and correspondence analysis. These methods will be applied to data from the 2000 Tennessee Youth Tobacco Survey.</p><p>The …
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Inference and robotic path planning over high dimensional categorical observations
… sparse, highdimensional categorical data. Statistical models, particularly in streaming and computationally constrained settings, have lagged behind data collection. Recent developments in topic modeling for robotics have highlighted the potential to efficiently extract …
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On the spatial modelling of mixed and constrained geospatial data
… from various sample spaces (e.g. continuous and categorical) is a common challenge for geoscience modellers and many geoscience applications such as evaluation of mineral resources, characterization of oil reservoirs or hydrology of groundwater. To consider the complex statistical and spatial …
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Inference and Robotic Path Planning over High Dimensional Categorical Observations
… sparse, high dimensional categorical data. Statistical models, particularly in streaming and computationally constrained settings, have lagged behind data collection. Recent developments in topic modeling for robotics have highlighted the potential to efficiently extract …
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Orthogonal models for cross-classified observations
… of constructing models for cross-classified categorical data. In particular we discuss the construction of a class of approximating models and the selection of the most suitable model in the class. Examples of application are used to illustrate the methodology. The main purpose of the thesis …
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Probabilistic Modeling of Multi-relational and Multivariate Discrete Data
… from multi-relational and multivariate discrete data is a crucial task that arises in many research and application domains, e.g. text mining, intelligence analysis, epidemiology, social science, etc. In this dissertation, we study and address three problems involving the modeling of …
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Empirical analysis of rough set categorical clustering techniques based on rough purity and value set
… homogeneous groups is a fundamental operation in data mining. Recently, attention has been put on categorical data clustering, where data objects are made up of non-numerical attributes. The implementation of several existing categorical clustering techniques is challenging as some are unable to …
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An investigation of the effect of different methods of patient management on the outcome of lithium therapy.
… of respective Medical Ethics Committees. Data was collected by patient interview, clinician questionnaire and from patients’ medical and/or psychiatric case notes. The data acquired was then used to generate and test overall indices for outcome, combining all aspects of lithium therapy, …
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The prevalence of atrial fibrillation in patients with ischaemic stroke in a district hospital in the Western Cape
… at Mitchell’s Plain Hospital in Cape Town and data was collected over a year. Patients diagnosed with a stroke were identified from an electronic patient register and relevant radiology and clinical data was sourced retrospectively. The diagnosis of ischaemic stroke was confirmed by a CT scan …
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