Modeliranje pojavnosti endemske nefropatije logističkom regresijom

master's thesis

• Author: Maja Šekoranja
• Mentor: Anamarija Jazbec (mentor)
• Committee member: Anamarija Jazbec (predsjednik povjerenstva)
• Committee member: Nikola Sarapa (član povjerenstva)
• Committee member: Nela Bosner (član povjerenstva)
• Committee member: Pavle Goldstein (član povjerenstva)
• Granter: University of Zagreb; Faculty of Science; (Department of Mathematics); Zagreb
• Defense date and country: 2015-07-13, Croatia
• Scientific / art field, discipline and subdiscipline: NATURAL SCIENCES; Mathematics

Abstract

U ovome radu modeliramo pojavnost endemske nefropatije logističkom regresijom. Promatramo modele nastale "FORWARD", "BACKWARD" i "STEPWISE" metodom selekcije, te zadani model i njegove varijacije. Statistička obrada podataka rađena je u statističkom paketu SAS Studio. U svakom modelu dobivenom SAS-ovim metodama selekcije kao rizični faktori za razvijanje endemske nefropatije pojavljuju se duljina života u endemskom selu, razina \(\alpha\)1 mikroglobulina te pozitivna obiteljska anamneza na endemsku nefropatiju.

Abstract (english)

In this thesis, we are modelling prevalence of endemic nephropathy with logistic regression. We are observing models which are created with "FORWARD", "BACKWARD" and "STEPWISE" selection methods, and also demanded model and its variations. Statistical analysis was done in statistical software SAS Studio. In each model created with SAS selection methods, living duration in endemic village, level of $\alpha$1 microglobulin and positive family history on endemic nephropathy are appearing as risk factors for developing an endemic nephropathy.

• Keywords: endemska nefropatija; logistička regresija; statistički paket SAS Studio
• Keywords (english): endemic nephropathy; logistic regression; statistical software SAS Studio
• Language: croatian
• URN:NBN: urn:nbn:hr:217:564721
• Study programme: Title: Mathematical Statistics; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra matematike (magistar/magistra matematike)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2019-02-13 10:01:47