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Applying Conditional Distributions To Individuals: Using Latent Variable Models, Feng Ji
Applying Conditional Distributions To Individuals: Using Latent Variable Models, Feng Ji
Theses and Dissertations
This study proposes a new method to interpret individual results of psychological test batteries. The Mahalanobis distance is a commonly-used measure of how unusual an individual’s profile of scores is compared to a population of score profiles. In models in which there is a set of predictors and a set of dependent variables (e.g., cognitive abilities predicting academic abilities), it is useful to distinguish between a profile of dependent scores that is unusual because its profile of predictor scores is unusual and a profile of dependent scores that is unusual even after controlling for the predictors. The conditional Mahalanobis distance …
Determining The Relationship Between Aging And Oxidative Stress In A Drosophila Melanogaster P38 Kb Framework, Aleksandra J. Majewski
Determining The Relationship Between Aging And Oxidative Stress In A Drosophila Melanogaster P38 Kb Framework, Aleksandra J. Majewski
Theses and Dissertations
Aging is inevitable for all organisms and can be characterized by degeneration of tissue, adecrease in motor function, and impaired stress response. In humans, it is often accompanied by an increased propensity for age related diseases. While all adults experience biological aging (senescence) not all adults experience age-associated disease. Thus, we claim these are not normal prospects of aging. Although the implications of aging are well understood, the molecular underpinnings for these processes remain elusive. As advances in medical science have been successful at prolonging lifespan, they concurrently extend the amount of time spend in diseased states. If we wish …
Clustering Biological Data With Self-Adjusting High-Dimensional Sieve, Josselyn Gonzalez
Clustering Biological Data With Self-Adjusting High-Dimensional Sieve, Josselyn Gonzalez
Theses and Dissertations
Data classification as a preprocessing technique is a crucial step in the analysis and understanding of numerical data. Cluster analysis, in particular, provides insight into the inherent patterns found in data which makes the interpretation of any follow-up analyses more meaningful. A clustering algorithm groups together data points according to a predefined similarity criterion. This allows the data set to be broken up into segments which, in turn, gives way for a more targeted statistical analysis. Cluster analysis has applications in numerous fields of study and, as a result, countless algorithms have been developed. However, the quantity of options makes …