Search for dissertations about: "Interval-censored data"

Found 3 swedish dissertations containing the words Interval-censored data.

  2. 1. Methods for interval-censored data and testing for stochastic dominance

    Author : Angel G. Angelov; Magnus Ekström; Maria Karlsson; Bengt Kriström; Per Johansson; Umeå universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Interval-censored data; Informative censoring; Self-selected intervals; Questionnaire-based studies; Maximum likelihood; Permutation test; Two-sample test; Stochastic dominance; Four-decision test; Statistics; statistik;

    Abstract : This thesis includes four papers: the first three of them are concerned with methods for interval-censored data, while the forth paper is devoted to testing for stochastic dominance.In many studies, the variable of interest is observed to lie within an interval instead of being observed exactly, i.e. READ MORE

  4. 2. EM Estimation in Phase Type Models

    Author : Marita Olsson; Göteborgs universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; phase type distributions; coxian distribution; EM algorithm; I-divergence; density estimation; right censoring; interval censoring; standard error estimation; asymptotic theory; jackknife; relapse clinical trials; survival data; hidden Markov chain; I-divergence;

    Abstract : This thesis consists of four articles whose theme in common is the class of phase type distributions. In the first article an EM algorithm is presented to estimate the parameters of a phase type distribution of fixed order. Also, it is shown that the algorithm can be used to approximate other continuous distributions by phase type distributions. READ MORE

  5. 3. Pharmacometric evaluation and improvement of models and study designs - applied in diabetes

    Author : Moustafa M. A. Ibrahim; Mats O. Karlsson; Maria C. Kjellsson; Paolo Magni; Uppsala universitet; []
    Keywords : MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES;

    Abstract : Pharmacometric models are increasingly used to improve the efficiency of the drug development process and increase our understanding of the studied underlying pathophysiological system. These models require assumptions for handling different types of data and the different model components, and the appropriateness of such assumptions must be carefully inspected for unbiased conclusions. READ MORE