基于广义线性混合模型的牛蜱抗药性比较研究

Q4 Medicine
A. Maiorano, T. S. Mota, A. Verdugo, R. Faria, B. P. M. Silva, M. C. Oliveira, J. Cyrillo, J. Silva
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引用次数: 2

摘要

采用Poisson -负二项分布的广义线性混合模型(glmm)比较了印度牛(bolus indicus, Nelore)和印度牛(bolus Simmental和Caracu)亚种的蜱虫抗性。众所周知,牛类动物(NE)比金牛座金牛具有更大的抵抗力。Simmental (SI)和Caracu (CA)品种的蜱虫抗性差异此前从未报道过。采用三种人工蜱害方法评价这些品种的蜱抗药性。本研究的统计点是显示蜱虫计数数据评估的替代模型,即glmm。采用负二项分布的GLMM法分析蜱类耐药性的研究尚未见报道。利用SAS程序中的PROC GLIMMIX程序进行分析。结果表明,负二项分布的GLMM适合于评价超过零观测值的蜱虫计数数据,避免了过度分散问题。最后,通过与Bonferroni试验的多次比较,发现不同品种的蜱虫侵害模式不同,表明NE是最具抗性的品种,其次是CA。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
COMPARATIVE STUDY OF CATTLE TICK RESISTANCE USING GENERALIZED LINEAR MIXED MODELS
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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来源期刊
Revista Brasileira de Biometria
Revista Brasileira de Biometria Agricultural and Biological Sciences-Agricultural and Biological Sciences (all)
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