Search for dissertations about: "linear mixed models"
Showing result 1 - 5 of 153 swedish dissertations containing the words linear mixed models.
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1. On Estimation and Prediction in Linear Mixed Models : A new approach to studying equal BLUEs and BLUPs
Abstract : Linear mixed models (LMMs) are widely used to analyze repeated, longitudinal, or clustered data in many disciplines, such as biology, medicine, psychology, sociology, economics, etc. One of the essential components of a linear mixed model is its covariance structure, i.e. READ MORE
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2. Benefits of Non-Linear Mixed Effect Modeling and Optimal Design : Pre-Clinical and Clinical Study Applications
Abstract : Despite the growing promise of pharmaceutical research, inferior experimentation or interpretation of data can inhibit breakthrough molecules from finding their way out of research institutions and reaching patients. This thesis provides evidence that better characterization of pre-clinical and clinical data can be accomplished using non-linear mixed effect modeling (NLMEM) and more effective experiments can be conducted using optimal design (OD). READ MORE
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3. Pharmacometric Investigations of Prediction Precision and Advances of Models for Composite Scale Data
Abstract : Clinical trials are needed to evaluate new treatments. In late-stage clinical trials, failures are mostly due to lack of efficacy. Fit-for-purpose analysis methods will likely increase the success rates and advance drug development by providing higher precision to support decisions such as go/no-go, dose selection, or sample size. READ MORE
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4. Generalised linear models with clustered data
Abstract : In situations where a large data set is partitioned into many relativelysmall clusters, and where the members within a cluster have some common unmeasured characteristics, the number of parameters requiring estimation tends to increase with sample size if a fixed effects model is applied. This fact causes the assumptions underlying asymptotic results to be violated. READ MORE
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5. Generalized linear models with clustered data
Abstract : In situations where a large data set is partitioned into many relatively small groups, and where the members within a group have some common unmeasured characteristics, the number of parameters requiring estimation tends to increase with sample size if a fixed effects model is applied. This fact causes the assumptions underlying asymptotic results to be violated. READ MORE