A Generalized Concordance Correlation Coefficient Based on the Variance Components Generalized Linear Mixed Models for Overdispersed Count Data

Biometrics ◽  
2009 ◽  
Vol 66 (3) ◽  
pp. 897-904 ◽  
Author(s):  
Josep L. Carrasco
2019 ◽  
Vol 37 (1) ◽  
pp. 41
Author(s):  
Amanda Marchi MAIORANO ◽  
Thiago Santos MOTA ◽  
Ana Carolina VERDUGO ◽  
Ricardo Antonio da Silva FARIA ◽  
Beatriz Pressi Molina da SILVA ◽  
...  

Comparison of tick resistance in Bos taurus indicus (Nelore) and Bos taurus taurus (Simmental and Caracu) subspecies was investigated utilizing generalized linear mixed models (GLMMs) with Poisson and Negative binomial distributions. Nelore animals (NE) are known to present greater resistance than t. taurus. Difference between tick resistance in Simmental (SI) and Caracu (CA) breeds has never been reported previously. Three artificial tick infestations were conducted to evaluate tick resistance in these breeds. The statistic point of the present study was to show alternative models for the evaluation of tick count data, the GLMMs. Analysis for tick resistance by GLMM with Negative binomial distribution has never been assessed previously. The analyses were performed by the use of the PROC GLIMMIX procedure of the SAS program. The results showed that GLMM with Negative binomial distribution is appropriated to evaluate tick count data with excess of zero observations avoiding overdispersion problems. Finally, considering multiple comparisons with the Bonferroni test, different pattern of tick infestation was observed for the studied breeds, suggesting that NE is the most resistant breed followed by CA.


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