Diagnostics for Overdispersion
提出诊断工具，用于评估额外二项或额外泊松变异对解释变量的依赖，并比较几种常见的过度离散模型，基于双指数族和伪似然公式的得分检验，利用平方残差进行图形和数值分析。
Abstract Diagnostic tools are proposed for assessing the dependence of extrabinomial or extra-Poisson variation on explanatory variables and for comparing several common models for overdispersion. These tools are based on tests for regression terms in the dispersion parameter of a generalized linear model, using double exponential family and “pseudolikelihood” formulations. Score tests do not require the full fitting of models for variation and lead to easy graphical and numerical procedures based on squared residuals (deviance or Pearson). Robust modifications of these are motivated by Levene's test in linear models. The diagnostic tools are intended primarily to ensure prudent modeling of the variance to make correct inferences about parameters in the mean.