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 7 of 7 for “"ordinal outcome"”.
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Stereotype Logit Models for High Dimensional Data
… the need for methods capable of handling an ordinal outcome in the presence of a high dimensional covariate space. In this research we present a method that combines the stereotype regression model (Anderson, 1984) with an elastic net penalty (Friedman et al., 2010) as a method capable of …
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Essays on the econometrics of ordinal data
In economics, ordinal variables like general health, mental health, and happiness level play a crucial role. Ordinal data is commonly used in surveys and questionnaires due to its ordered structure. However, incorporating an ordinal outcome variable in economic studies presents challenges. The …
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Problems in Pedigrees and Phylogenies
… estimation using pedigree data, with an ordinal outcome trait. We discuss the use of the threshold model for heritability estimation, exploring the consequences of model misspecification and sample size requirements under this model. Next, we move to phylogenetic methods for the detection …
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Statistical methodologies for network meta-analysis with applications in veterinary medicine
… In Chapter 2, we propose an NMA model for an ordinal outcome that allows for outcome categorizations to vary across trials. It is common for the reporting of ordinal outcomes to differ from trial to trial, and the proposed model allows for data from all available trials to contribute to …
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Joint Models for Longitudinal Analysis and Competing Risks in Survival Analysis
In longitudinal studies involving assessing ordinal disease(s) outcome across multiple time points, ignoring the correlations between the development and transition of the disease status and any informative potential censoring event(s) may lead to bias in the estimation of covariate effects. To …
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The Relation between Uncertainty in Latent Class Membership and Outcomes in a Latent Class Signal Detection Model
Latent class variables are often used to predict outcomes. The conventional practice is to first assign observations to one of the latent classes based on the maximum posterior probabilities. The assigned class membership is then treated as an observed variable and used in predicting the outcomes. …
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SENSITIVITY ANALYSIS – THE EFFECTS OF GLASGOW OUTCOME SCALE MISCLASSIFICATION ON TRAUMATIC BRAIN INJURY CLINICAL TRIALS
I. EFFECTS OF GLASGOW OUTCOME SCALE MISCLASSIFICATION ON TRAUMATIC BRAIN INJURY CLINICAL TRIALS The Glasgow Outcome Scale (GOS) is the primary endpoint for efficacy analysis of clinical trials in traumatic brain injury (TBI). Accurate and consistent assessment of outcome after TBI is essential to …