dc.contributor.advisor Langaas, Mette dc.contributor.author Klevjer, Marie dc.date.accessioned 2019-09-11T11:19:33Z dc.date.created 2017-06-01 dc.date.issued 2017 dc.identifier ntnudaim:16075 dc.identifier.uri http://hdl.handle.net/11250/2616030 dc.description.abstract The purpose of this thesis was to investigate the relationship between the energy expenditure and the FTO genotype (Fat Mass And Obesity-Associated Protein) of 101 severely overweight persons. The statistical methods used involve linear regression with different representations of the energy expenditure as response and the FTO genotype as exposure. Further, other covariates were included in the regression. These covariates were selected using the best subset selection and penalisation through the Lasso approach. The model accuracy was examined through diagnostics plots, and a multi sample-split method was used to determine the $p$-values for the Lasso approach. When the diet induced energy expenditure was examined, a linear mixed model was used to correctly adjust for the dependencies in the data. A latent class linear mixed model was constructed to look for clustering between the individuals. None of these statistical analyses revealed a relationship between the energy expenditure and the FTO genotype for these 101 severely overweight persons. Sex and weight were the covariates that affected the energy expenditure the most. en dc.language eng dc.publisher NTNU dc.subject Lektorutdanning i realfag for trinn 8 -13, Matematikk og fysikk en dc.title Statistical modelling and analysis of energy expenditure among severely overweight en dc.type Master thesis en dc.source.pagenumber 112 dc.contributor.department Norges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi og elektroteknikk,Institutt for matematiske fag nb_NO dc.date.embargoenddate 10000-01-01
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