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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/15707

Title: Joint modelling of multiple outcomes on longitudinal behaviour of genetically modified mice
Authors: Bhuia, Mohammad Romel
Advisors: SHKEDY, Ziv
JACOBS, Tom
Issue Date: 2013
Publisher: tUL
Abstract: Aim of the study is to investigate the differences in the evolution over time between TauPS2APP and wild-type mice for the behaviour data. Moreover, to fit joint model combining outcomes in order to investigate if there is any benefit compared to a univariate analysis. Two datasets, extracted from a pre-clinical experiment on Alzheimer's disease, consisting information regarding 5 tests for different behaviours of young and old mice, are combined. Correlations among outcomes from same mouse are captured by modelling the responses jointly by fitting them pair-wise and combining the results using pseudo likelihood theory. Univariate generalized linear mixes models (GLMM) shows significant evidences of difference in the evolution over time between genotypes for all the behaviors of young mice as well as combined data. Multivariate joint model also shows the similar effect on overall responses. Effects of age and genotype are also significant.
Notes: Master of Statistics-Biostatistics
URI: http://hdl.handle.net/1942/15707
Category: T2
Type: Theses and Dissertations
Appears in Collections: Master theses

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