Regression of Area Mortality Rates on Explanatory Variables: What Weighting is Appropriate?
本文提出一种介于未加权和完全加权之间的最大似然回归方法，用于分析区域死亡率与解释变量的关系，考虑了抽样误差、解释变量和区域间未解释差异三种变异来源，并适用于logit死亡率、标准化死亡率比等指标。
"One can often gain insight into the aetiology of a disease by relating mortality rates in different areas to explanatory variables. Multiple regression techniques are usually employed, but unweighted least squares may be inappropriate if the areas vary in population size. Also, a fully weighted regression, with weights inversely proportional to binomial sampling variances, is usually too extreme. This paper proposes an intermediate solution via maximum likelihood which takes account of three sources of variation in death rates: sampling error, explanatory variables and unexplained differences between areas. The method is also adapted for logit (death rates), standardized mortality ratios (SMRs) and log (SMRs). Two [United Kingdom] examples are presented."