
SUMMARYThe binary variable is one of the most common types of variables in the analysis of income‐related health inequalities. I argue that while the binary variable has some unusual properties, it shares many of the properties of the ratio–scale variable and hence lends itself to both relative and absolute inequality analyses, albeit with some qualifications. I argue that criticisms of the normalization I proposed in an earlier paper, and of the use of the binary variable for inequality analysis, stem from a misrepresentation of the properties of the binary variable, as well as a switch of focus away from relative inequality to absolute inequality. I concede that my normalization is not uncontentious, but, in a way, that has not previously been noted. Copyright © 2011 John Wiley & Sons, Ltd.
Models, Statistical, 330, Social Class, Data Interpretation, Statistical, Humans, Health Status Disparities, Health Surveys
Models, Statistical, 330, Social Class, Data Interpretation, Statistical, Humans, Health Status Disparities, Health Surveys
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 125 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
