title: Regression of area mortality rates on explanatory variables:  what weighting is appropriate?
abstract: "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."
authors.forename: S J
authors.initials: SJ
authors.lastname: Pocock
authors.forename: D G
authors.initials: DG
authors.lastname: Cook
authors.forename: S A
authors.initials: SA
authors.lastname: Beresford
mesh_terms: D003710:Demography; D019049:Developed Countries; D005060:Europe; D009026:Mortality; D011153:Population; D011157:Population Dynamics; D012044:Regression Analysis; D012106:Research; D013223:Statistics as Topic; D006113:United Kingdom
keywords: Data Analysis; Demographic Factors; Developed Countries; Europe; Mortality; Northern Europe; Population; Population Dynamics; Research Methodology; Statistical Regression; Statistical Studies; United Kingdom