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master's thesis
Procjena genetske korelacije između binarne i normalne varijable koristeći GLIMMIX SAS proceduru
Zagreb: University of Zagreb, Faculty of Agriculture, 2019. urn:nbn:hr:204:288388
Ćosić, Mateja
University of Zagreb
Faculty of Agriculture
Animal Science

Institutional repository: Repository Faculty of Agriculture University of Zagreb

Cite this document

Ćosić, M. (2019). Procjena genetske korelacije između binarne i normalne varijable koristeći GLIMMIX SAS proceduru (Master's thesis). Zagreb: University of Zagreb, Faculty of Agriculture. Retrieved from https://urn.nsk.hr/urn:nbn:hr:204:288388

Ćosić, Mateja. "Procjena genetske korelacije između binarne i normalne varijable koristeći GLIMMIX SAS proceduru." Master's thesis, University of Zagreb, Faculty of Agriculture, 2019. https://urn.nsk.hr/urn:nbn:hr:204:288388

Ćosić, Mateja. "Procjena genetske korelacije između binarne i normalne varijable koristeći GLIMMIX SAS proceduru." Master's thesis, University of Zagreb, Faculty of Agriculture, 2019. https://urn.nsk.hr/urn:nbn:hr:204:288388

Ćosić, M. (2019). 'Procjena genetske korelacije između binarne i normalne varijable koristeći GLIMMIX SAS proceduru', Master's thesis, University of Zagreb, Faculty of Agriculture, accessed 26 December 2024, https://urn.nsk.hr/urn:nbn:hr:204:288388

Ćosić M. Procjena genetske korelacije između binarne i normalne varijable koristeći GLIMMIX SAS proceduru [Master's thesis]. Zagreb: University of Zagreb, Faculty of Agriculture; 2019 [cited 2024 December 26] Available at: https://urn.nsk.hr/urn:nbn:hr:204:288388

M. Ćosić, "Procjena genetske korelacije između binarne i normalne varijable koristeći GLIMMIX SAS proceduru", Master's thesis, University of Zagreb, Faculty of Agriculture, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:204:288388

Metadata
TitleProcjena genetske korelacije između binarne i normalne varijable koristeći GLIMMIX SAS proceduru
Title (english)Evalutation of genetic correlation between binary and normal variables using the GLIMMIX SAS procedure
AuthorMateja Ćosić
MentorMaja Ferenčaković (mentor)
Committee memberMaja Ferenčaković (predsjednik povjerenstva)
Committee memberVlatka Čubrić Čurik (član povjerenstva)
Committee memberIno Čurik (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Agriculture
(Animal Science)
Zagreb
Defense date and country2019-09-30, Croatia
Scientific / art field,
discipline and subdiscipline		BIOTECHNICAL SCIENCES
Agronomy
Abstract
Procjena genetske korelacije između dvije varijable koje imaju normalnu raspodjelu je uobičajena i može se napraviti bez većih poteškoća, dok se problem javlja kad varijable nemaju normalnu raspodjelu, kao što je binarna varijabla. U tom slučaju potrebno je koristiti generalizirani bivarijatni mješoviti model, a jedna od opcija je korištenje GLIMMIX procedure. GLIMMIX procedura je SAS procedura koja prilagođava modele podatcima koji nemaju normalnu raspodjelu. U radu su simulirani podatci uspješnosti koncepcije i težine kod starosti od 12 mjeseci 5000 krava, kćeri 50 bikova. Provedena je bivarijatna analiza između binarne (uspješnost koncepcije) i normalne (težina) varijable koristeći GLIMMIX proceduru. Radi usporedbe provedena je bivarijatna analiza tretirajući uspješnost koncepcije kao normalnu varijablu, te univarijatne analize za obje varijable. Kod analiza binarnih podataka korištene su logit i probit funkcije veze. Iz dobivenih rezultata analiza zaključeno je da tretiranjem binarne varijable kao normalne, ne dobivamo precizne procjene varijanci i kovarijanci, a time ni genetske korelacije. Stoga GLIMMIX procedura znatno olakšava ovakve složenije analize proširenjem mogućnosti generaliziranih mješovitih modela.
Abstract (english)
Genetic correlation estimation between two variables that have a normal distribution is common and can be done without much difficulty. The problem arises when one of the variables does not have a normal distribution, i.e. binary variable. In this case, a generalized bivariate mixed model should be used and GLIMMIX procedure can help here. The GLIMMIX procedure fits statistical models to data where the response is not necessarily normally distributed. In this master’s thesis, success of conception and weight of 5 000 cows that are 12 months old, daughters of 50 bulls, were simulated. A bivariate analysis was performed between binary (success of conception) and normal (weight) variables using GLIMMIX procedure. For comparison, bivariate analysis was performed treating success of conception as normal variable and univariate analysis for both variables. Logit and probit link functions were used for binary data analyzes. The results showed that, by treating binary variable as normal, did not lead to accurate estimates of variance and covariance, and thus genetic correlation. Therefore, the GLIMMIX procedure noticeably facilitates more complex analyzes by extending the abilities of generalized mixed models.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:204:288388
Study programmeTitle: Animal Genetics and Breeding
Study programme type: university
Study level: graduate
Academic / professional title: magistar/ magistra inženjer/inženjerka genetike i oplemenjivanja životinja (magistar/ magistra inženjer/inženjerka genetike i oplemenjivanja životinja)
Type of resourceText
File originBorn digital
Access conditionsAccess restricted to students and staff of home institution
Terms of useLicence In copyright icon
Created on2019-11-18 07:48:12