A Monte Carlo study of tests on data originating from quadrat sampling. I: Data from a Poisson distribution.
Computer simulations are used to examine the significance levels and powers of several tests which have been employed to compare the means of Poisson distributions. In particular, attention is focused on the behaviour of the tests when the means are small, as is often the case in ecological studies when populations of organisms are sampled using quadrats. Two approaches to testing are considered. The first assumes a log linear model for the Poisson data and leads to tests based on the deviance. The second employs standard analysis of variance tests following data transformations, including the often used logarithmic and square root transformations. For very small means it is found that a deviance-based test has the most favourable characteristics, generally outperforming analysis of variance tests on transformed data; none of the latter appears consistently better than any other. For larger means the standard analysis of variance on untransformed data performs well.
Bradley
J S
JS
School of Biological and Environmental Sciences, Murdoch University, Western Australia.
McKay
R J
RJ
D000704:Analysis of Variance; D003198:Computer Simulation; D016014:Linear Models; D009010:Monte Carlo Method; D016012:Poisson Distribution