A unified approach to model selection using the likelihood ratio test

作者：Fraser Lewis, Adam Butler, Lucy Gilbert · 发表于：Methods in Ecology and Evolution · 年份：2010 · DOI：10.1111/j.2041-210x.2010.00063.x · 被引用次数：321 · 研究领域：Species Distribution and Climate Change、Ecology and Vegetation Dynamics Studies、Data Analysis with R

Summary 1. Ecological count data typically exhibit complexities such as overdispersion and zero‐inflation, and are often weakly associated with a relatively large number of correlated covariates. The use of an appropriate statistical model for inference is therefore essential. A common selection criteria for choosing between nested models is the likelihood ratio test (LRT). Widely used alternatives to the LRT are based on information‐theoretic metrics such as the Akaike Information Criterion. 2. It is widely believed that the LRT can only be used to compare the performance of nested models – i.e. in situations where one model is a special case of another. There are many situations in which it is important to compare non‐nested models, so, if true, this would be a substantial drawback of using LRTs for model comparison. In reality, however, it is actually possible to use the LRT for comparing both nested and non‐nested models. This fact is well‐established in the statistical literature, but not widely used in ecological studies. 3. The main obstacle to the use of the LRT with non‐nested models has, until relatively recently, been the fact that it is difficult to explicitly write down a formula for the distribution of the LRT statistic under the null hypothesis that one of the models is true. With modern computing power it is possible to overcome this difficulty by using a simulation‐based approach. 4. To demonstrate the practical application of the LRT to both nested and non‐n...