Measuring inequality in self‐reported health—discussion of a recently suggested approach using Finnish data
评估了将自评健康序数数据转化为基数数据的不同方法（如OLS、有序probit和区间回归），并用芬兰数据计算收入相关健康不平等指数，验证了区间回归法优于其他方法，但发现不平等程度对所选缩放工具敏感。
Health surveys often include a general question on self-assessed health (SAH), usually measured on an ordinal scale with three to five response categories, from 'very poor' or 'poor' to 'very good' or 'excellent'. This paper assesses the scaling of responses on the SAH question. It compares alternative procedures designed to impose cardinality on the ordinal responses. These include OLS, ordered probit and interval regression approaches. The cardinal measures of health are used to compute and decompose concentration indices for income-related inequality in health. Results are provided using Finnish data on 15D and the SAH questions. Further evidence emerges for the internal validity of a method used in a pioneering study by van Doorslaer and Jones which was based on Canadian data on the McMaster Health Utility Index Mark III (HUI) and SAH. The study validates the conclusions drawn by van Doorslaer and Jones. It confirms that the interval regression approach is superior to OLS and ordered probit regression in assessing health inequality. However, regarding the choice of scaling instrument, it is concluded that the scaling of SAH categories and, consequently, the measured degree of inequality, are sensitive to characteristics of the chosen scaling instrument.