Search for dissertations about: "non-normal data"
Showing result 1 - 5 of 6 swedish dissertations containing the words non-normal data.
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1. Some Aspects on Confirmatory Factor Analysis of Ordinal Variables and Generating Non-normal Data
Abstract : This thesis, which consists of five papers, is concerned with various aspects of confirmatory factor analysis (CFA) of ordinal variables and the generation of non-normal data. The first paper studies the performances of different estimation methods used in CFA when ordinal data are encountered. READ MORE
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2. Optimal (Adaptive) Design and Estimation Performance in Pharmacometric Modelling
Abstract : The pharmaceutical industry now recognises the importance of the newly defined discipline of pharmacometrics. Pharmacometrics uses mathematical models to describe and then predict the performance of new drugs in clinical development. READ MORE
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3. Aspects of foreign-born women's health and childbirth-related outcomes : an epidemiological study of women of childbearing age in Sweden
Abstract : This thesis aims to study the association between aspects of health and childbirth-related outcomes and country of birth. A theoretical model has been developed from a feministic perspective to reflect foreign-born women's risk of poor health and childbirth-related outcomes in a broader context. READ MORE
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4. Population Pharmacodynamic Modeling and Methods for D2-receptor Antagonists
Abstract : Early predictions of a potential drug candidate’s time-course of effect and side-effects, based on models describing drug concentrations, drug effects and disease progression, would be valuable to make drug development more efficient. Pharmacodynamic modeling can incorporate and propagate prior knowledge and be used for simulations of different scenarios. READ MORE
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5. Bayesian Modeling of Conditional Densities
Abstract : This thesis develops models and associated Bayesian inference methods for flexible univariate and multivariate conditional density estimation. The models are flexible in the sense that they can capture widely differing shapes of the data. The estimation methods are specifically designed to achieve flexibility while still avoiding overfitting. READ MORE