A statistical test for differences in sexual dimorphism between populations

Relethford, John H.; Hodges, Denise C.

doi:10.1002/ajpa.1330660105

Cited by 43 publications

(28 citation statements)

References 9 publications

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“…It would seem that either test is applicable, as should be expected from Relethford and Hodges' (1985) systematic development of their test from linear regression analysis and the equally systematic development of a ttest from considerations of differences between distributions that has been presented here. This expectation is further comfirmed by a mathematical comparison of TRH and Tg.…”

Section: Methodsmentioning

confidence: 93%

“…EMPIRICAL APPLICATION Relethford and Hodges (1985) apply their ttest (TRH) that is derived from linear regression using sex as dummy variables to two test cases using sample sizes, mean values, and standard deviations already published. These are 1) a comparison of sexual dimorhism between a n Irish population and a Colombian population and 2) a comparison of sexual dimorphism between two generations of the same population in Poland.…”

Section: Methodsmentioning

confidence: 99%

“…It is compared with the t-test derived by Relethford and Hodges (1985), which was based upon linear regression with sex as a dummy variable. Both are determined to be mathematically equivalent, though the one derived here is more similar in form to traditional t-tests of differences and therefore may be simpler to employ.…”

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confidence: 99%

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Comparison of t‐tests for differences in sexual dimorphism between populations

Greene

1989

American J Phys Anthropol

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A t-test that can be used for evaluating the significance of differences in metric sexual dimorphism between populations is derived directly from mathematical considerations of the differences between distributions. It is compared with the t-test derived by Relethford and Hodges (1985), which was based upon linear regression with sex as a dummy variable. Both are determined to be mathematically equivalent, though the one derived here is more similar in form to traditional t-tests of differences and therefore may be simpler to employ. Both tests require only summary statistics for comparisons between populations and comparisons between generations within populations.Relethford and Hodges (1985) point out that while the analysis of sexual dimorphism in human and nonhuman primate populations has become a n important topic, few studies have tested the significance of sexual dimorphism between populations. Those that have attempted to do so have used involved procedures that often require computations based upon raw data rather than on summary statistics.For example, Bennett (1981) developed a technique based upon first deleting the area of overlap between the male and female distributions ofa quantitative variable in a population. This area represents those individuals who in terms of the variable could be classified as either male or female. Second, he used the percentage of areas remaining under the distribution curves, male and female, to quantify sexual dimorphism within the population. Then, finally, these percentages were compared between populations using a t-test based upon arcsin transformations of the percentages found in each population.Chakraborty and Majumder (1982), while criticizing Bennett's statistical assumptions, developed another technique that is also based upon the areas of nonoverlap between male and female distributions of quantitative characteristics. They, unlike Bennett, in addition derived a standard error for their statistic.Relethford and Hodges suggest that a test of significance based upon s;mmary statistics, and therefore not requiring the raw data needed to generate the distributions required in Bennett's and Chakraborty and Majumder's techniques, would be valuable for those who are interested in comparatively studying sexual dimorphism between populations or over time periods. Since many of the extant publications on metric variation only contain sample sizes, means, and standard deviations, the utility of such a test is obvious.They then developed a t-test for testing the significance of sexual dimorphism between samples from different populations that is based upon the relationship of t-tests to a version of linear regression with sex as a dummy variable. Essentially, if a metric variable is regressed upon sex in two different populations, then a t-test for the equality of slopes between the resulting regression lines can be used for assessing the significance of differences in sexual dimorphism. They demonstrate mathematically, following

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Section: Methodsmentioning

confidence: 93%

Section: Methodsmentioning

confidence: 99%

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Comparison of t‐tests for differences in sexual dimorphism between populations

Greene

1989

American J Phys Anthropol

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“…Statistical significance of SSD within and between groups was assessed following the procedure described by Relethford and Hodges (1985). To determine whether the SSD within the sample was statistically significant we used a t test derived from the linear regression of the natural logarithm of mean height on sex (dummy variables were used for sex, assigning a value of 0 for females and 1 for males).…”

Section: Methodsmentioning

confidence: 99%

Ontogeny of sexual size dimorphism and environmental quality in Guatemalan children

Nikitovic

Bogin

2013

American J Hum Biol

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“…However, statistical tests (two-way unbalanced ANOVA and MANOVA) can be used to evaluate the hypothesis that the degree of dimorphism varies among groups (Greene, 1989;Hamilton, 1982;Relethford and Hodges, 1985;Sokal and Rohlf, 1981). Konigsberg (1991) has discussed anthropological applications of this model to multivariate problems and presents a general discussion of its mathematical foundations (see also Key and Jantz, 1981).…”

Section: Introductionmentioning

confidence: 99%

A re‐evaluation of subspecific variation and canine dimorphism in woolly spider monkeys (Brachyteles arachnoides)

Jungers

1994

American J Phys Anthropol

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A recent study suggests that differing populations of woolly spider monkeys exhibit a substantial degree of morphological, cytogenetic, and behavioral variation. We re-evaluate the differences between populations in the degree of canine tooth height sexual dimorphism and in the frequency of thumbs. Statistical analysis of variation in the degree of canine sexual dimorphism between these populations fails to provide strong evidence for subspecific variation: differences in the degree of canine dimorphism cannot be considered statistically significant. Differences between populations in the frequency of thumbs are, however, statistically significant. The lack of clear distinctions between populations in the degree of canine dimorphism complicates assessments of behavioral variation between these populations. We suggest that the level of geographic variation in woolly spider monkey canine dimorphism is not consistent with subspecific status.

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A statistical test for differences in sexual dimorphism between populations

Cited by 43 publications

References 9 publications

Comparison of t‐tests for differences in sexual dimorphism between populations

Comparison of t‐tests for differences in sexual dimorphism between populations

Ontogeny of sexual size dimorphism and environmental quality in Guatemalan children

A re‐evaluation of subspecific variation and canine dimorphism in woolly spider monkeys (Brachyteles arachnoides)

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