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Master's Dissertation
DOI
Document
Author
Full name
Juliana Di Giorgio Giannotti
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
Piracicaba, 2000
Supervisor
Title in Portuguese
Meta-análise de estimativas da correlação genética entre pesos ao nascer e desmama de bovinos
Keywords in Portuguese
BOVINOS DE CORTE
CORRELAÇÃO GENÉTICA
DESMAMA
GADO ZEBU
PESO
Abstract in Portuguese
Uma meta-análise foi conduzida com o objetivo de resumir de modo mais apropriado as estimativas da correlação genética entre pesos ao nascer e desmama de bovinos de corte de origem zebuína. Foi usado um conjunto de estimativas obtidas em 39 trabalhos publicados no período de 1968 a 2000. Estes dados foram analisados de acordo com modelos fixo e aleatório, este último sob as técnicas da máxima verossimilhança restrita e método dos momentos. Para a situação específica deste estudo, observou-se que o modelo fixo não foi apropriado em virtude da falta de homogeneidade das estimativas de correlação, sendo portanto recomendável o modelo aleatório. A análise de subgrupo indicou heterogeneidades dos estudos. Conclui-se que a meta-análise constitui-se em técnica que deve ser implementada para esta e outras finalidades
Title in English
Meta-analysis of estimates of genetic correlation between birth and weaning weigths in zebu cattle
Abstract in English
A meta-analysis was conducted to summarize published estimates of genetic correlation between birth and weaning weight of zebu cattle. It was used a collection of estimates from 39 reports from 1968 to 2000. Data were analyzed under fixed and random effect models. Components of variance were obtained by the method of moments and restricted maximum likelihood techniques. For the actual case it was verified a strong lack of homogeneity among the studies considered. As a consequence fixed model estimates of combined results were inappropriate. Results suggest random effects model produced better estimates. Subgroup comparisons showed heterogeneity of studies. It was conclude that meta-analysis techniques were recommended for quantitative reviews of genetic parameters
 
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Publishing Date
2019-11-08
 
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