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A multinomial model for cross classified data with a measure of dependency

 

作者: Jeffrey R. Wilson,   David L. Turner,  

 

期刊: Journal of Applied Statistics  (Taylor Available online 1990)
卷期: Volume 17, issue 1  

页码: 115-124

 

ISSN:0266-4763

 

年代: 1990

 

DOI:10.1080/757582651

 

出版商: Carfax Publishing Company

 

数据来源: Taylor

 

摘要:

This paper presents a modified multinomial model for analyzing behaviour among wildlife populations. It assumes that the covariance matrix of the observed proportions is a multiple of the covariance matrix under simple random sampling. The model also allows a measure of dependency among the clusters within subpopulations, a type of dependency that assumes the relationships among units are the same for any two units. In addition, this paper illustrates the fact that the incorrect application of the Pearson chi-square statistic based on simple random sampling can produce misleading results when frequencies are obtained from a non-multinomial sampling scheme. Data obtained from a study of wild turkeys are analyzed using the proposed multinomial model.

 

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