The Bias of combining variables on fish's aggressive behavior studies.

2019

Made available in DSpace on 2019-10-06T16:27:42Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-07-01 Quantifying animal aggressive behavior by behavioral units, either displays or attacks, is a common practice in animal behavior studies. However, this practice can generate a bias in data analysis, especially when the variables have different temporal patterns. This study aims to use Bayesian Hierarchical Linear Models (B-HLMs) to analyze the feasibility of pooling the aggressive behavior variables of four cichlids species. Additionally, this paper discusses the feasibility of combining variables by examining the usage of different sample sizes and family distributions to aggressive …