Least-False and Local Misspecification Methods for Longitudinal Data with Dropout Amal A. Almohisen Thesis submitted for the degree of Doctor of Philosophy School of Mathematics & Statistics Newcastle University Newcastle upon Tyne United Kingdom March

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dc.contributor.advisorRobin Henderson
dc.contributor.authorAMAL ABDULLAH ALI ALMOHISEN
dc.date2017
dc.date.accessioned2022-05-29T13:19:24Z
dc.date.available2022-05-29T13:19:24Z
dc.degree.departmentSTATISTICS
dc.identifier.other32970
dc.identifier.urihttps://drepo.sdl.edu.sa/handle/20.500.14154/48121
dc.publisherSaudi Digital Library
dc.titleLeast-False and Local Misspecification Methods for Longitudinal Data with Dropout Amal A. Almohisen Thesis submitted for the degree of Doctor of Philosophy School of Mathematics & Statistics Newcastle University Newcastle upon Tyne United Kingdom March
dc.typeThesis
sdl.thesis.levelDoctoral
sdl.thesis.sourceSACM - United Kingdom

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