Empirical comparison of distance equations using discrete traits
Bibliographic Data
| ID | 8319331 |
|---|---|
| Authors | Michael Finnegan (0009-0003-4646-6471, Kansas State University), Kevin Cooprider (Kansas State University) |
| Year | 1978 |
| Volume | 49 |
| Issue | 1 |
| Pages | 39-46 |
| Publication date | 1978-07-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | American Journal of Physical Anthropology (JOURNAL) |
| Journal identifiers | ISSN: 0002-9483 • E-ISSN: 1096-8644 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/ajpa.1330490108 |
| PMID | 677296 |
| OpenAlex | W2018804259 |
| Language | EN |
| Citations received | 15 |
| References cited | 11 |
The use of the Grewal‐Smith statistic in measuring biological distance among skeletal population samples has been questioned since it was first applied to human populations. Recently, in an attempt to stabilize the variance of the Grewal‐Smith statistic for use with non‐metric analysis, Sjøvold ('73) and Green and Suchey ('76) have introduced corrections and alternative transformations which may enhance the meaning of biological distance among population samples. Their recommendations improve the statistics for specific variable ranges; i.e., small sample size and low trait frequencies. Thirteen equations representing Grewal‐Smith, Freeman‐Tukey, Anscombe, and Bartlett transformations and/or corrections, were compared using rank order correlation statistics on actual biological distances generated by real population data as presented in existing literature. Results from testing these actual distance models show little variation between equations based on the populational data sets used. Based on these findings, the distance model resulting from the Grewal‐Smith statistic is not inferior to the more sophisticated models, although the latter may be superior by allowing specific improvements for small sample size and/or low trait frequencies
Econometrics · Statistics · Computer Science · Energy, Environment, Agriculture Analysis · Mathematics · Numerical methods in inverse problems
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| Unique citing works | 15 |
|---|---|
| Citations per year | 0,32 |
| Citation span | 1979 - 2023 (45) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 13 |