Search for dissertations about: "mixed-model study"
Showing result 1 - 5 of 39 swedish dissertations containing the words mixed-model study.
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1. Cognitive Automation in Mixed-Model Assembly Systems
Abstract : AbstractCustomization and personalization of products and services has become the new standard of doing business. In order to provide highly customized products at a reasonable price flexible processes are needed. READ MORE
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2. Meaning-Making Variations in Acculturation and Ritualization : A multi-generational study of Suroyo migrants in Sweden
Abstract : This dissertation focuses on how acculturation affects meaning-making among three generations of Suroye in the city of Södertälje, Sweden. Special focus is on youth. An inter-disciplinary and a mixed-model approach is used, with the purpose to contribute to research knowledge on meta, theoretical, methodological, and empirical levels. READ MORE
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3. Novel Statistical Methods in Quantitative Genetics : Modeling Genetic Variance for Quantitative Trait Loci Mapping and Genomic Evaluation
Abstract : This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. READ MORE
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4. Learning psychotherapy : An effectiveness study of clients and therapists
Abstract : Background Many psychotherapy studies with trainees have been conducted, but few have investigated how effective baseline trainee-led psychotherapies are. Baseline trainee-led psychotherapies are often provided by a professional education, and the therapists are often young, untrained and inexperienced. READ MORE
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5. Regression on high-dimensional predictor space : with application in chemometrics and microarray data
Abstract : This thesis focuses on regression methodology for prediction and classification in situations where there are many predictors but limited number of observations. This situation is common in chemometrics and microarray data. READ MORE