Relationship between the <scp>2D</scp>:<scp>4D</scp> and prenatal testosterone, adult level testosterone, and testosterone change: Meta‐analysis of 54 studies

Sorokowski, Piotr; Kowal, Marta

doi:10.1002/ajpa.24852

Cited by 3 publications

(1 citation statement)

References 133 publications

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“…Based on our experiences, we think that there are three major reasons why ratios are still used for normalization/standardization: (i) ratios are indeed very simple to calculate and are thus intuitively appealing, which gives the impression that they are simple to interpret, which is not at all true; (ii) a tradition in a given field that is difficult to abandon, as researchers tend to use a technique they learned during their training. This may include the use of the second-to fourth-digit ratio in biological anthropology (for recent meta-analysis, see [31]), which is still very common, although it was previously criticized [12,32]; and (iii) a lack of proper mathematical knowledge about functions. The problems with ratios are often not included in practical statistical/mathematical courses.…”

Section: Why Are Per Capita Ratios Still So Prevalent?mentioning

confidence: 99%

The fallacy of global comparisons based on per capita measures

Kratochvíl,

Havlíček

2024

R. Soc. Open Sci.

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Media, social scientists and public health researchers often present comparisons across countries, and policy makers use such comparisons to take evidence-based action. For a meaningful comparison among countries, one often needs to normalize the measure for differences in population size. To address this issue, the first choice is usually to calculate per capita ratios. Such ratios, however, normalize the measure for differences in population size directly only under the highly restrictive assumption of a proportional increase of the measure with population size. Violation of this assumption frequently leads to misleading conclusions. We compare per capita ratios with an approach based on regression, a widely used statistical procedure that eliminates many of the problems with ratios and allows for straightforward data interpretation. It turns out that the per capita measures in three global datasets (gross domestic product, COVID-19-related mortality and CO 2 production) systematically overestimate values in countries with small populations, while countries with large populations tend to have misleadingly low per capita ratios owing to the large denominators. Unfortunately, despite their biases, comparisons based on per capita ratios are still ubiquitous, and they are used for influential recommendations by various global institutions. Their continued use can cause significant damage when employed as evidence for policy actions and should therefore be replaced by a more scientifically substantiated and informative method, such as a regression-based approach.

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Section: Why Are Per Capita Ratios Still So Prevalent?mentioning

confidence: 99%