Calculate stature estimation according to: Vercellotti et al. 2009
Source:R/vercellotti_etal_2009.R
vercellotti_etal_2009.RdStature estimation (mm) based on the hierarchy of different regression calculations, separated by sex developed for 60 individuals from a medieval (XI-XII c) cemetery in Giecz, Poland (Vercellotti et al. 2009). Bone measures used: Fem2+Tib1, Fem2, Fem1, Tib1, Hum1+Rad1, Hum1, Rad1 The addition of individual bone measurements is performed during the calculation.
If bone measures for left and right are provided the mean value will be used, but for statistic information 2 bones will be counted (n_measures). Vercellotti et al. propose regression calculations for the combination of male and female individuals. These regressions will be used in case of undetermined sex (indet.).
Returns a data.frame with:
ind: individual identifyer (rownames),
sex: as provided for calculation: m, f, indet.
stature: estimated on the provided sex and bone measures,
bone (measure(s)): bones used for calculation,
if_female (stature): columns with alternative stature for three sex classes,
if_male (stature),
if_indet. (stature) and
n_measures: number of bone measures included: e.g. 2 Fem2 (left, right) + 1 Tib1
References
Vercellotti G, Agnew AM, Justus HM, Sciulli PW (2009). “Stature estimation in an early medieval (XI-XII c.) Polish population: Testing the accuracy of regression equations in a bioarcheological sample.” American Journal of Physical Anthropology, 140(1), 135–142. ISSN 1096-8644, doi:10.1002/ajpa.21055 .
Author
Hendrik Raese h.raese@ufg.uni-kiel.de
Christoph Rinne crinne@ufg.uni-kiel.de
Anna Loy aloy@roots.uni-kiel.de
Nils Müller-Scheeßel nils.mueller-scheessel@ufg.uni-kiel.de
Examples
# Read example dataset into a data frame.
x <- statuAAR::TrotterGleser1952
x <- x[x$Race == "White", ]
#'
# Create & check the data frame of mesures concordance for Trotter & Gleser 1952
measures.concordance <- create.measures.concordance()
measures.concordance[measures.concordance$own != "",]
#> short long own
#> 1 Fem1 Femur.1 Fem
#> 10 Hum1 Humerus.1 Hum
#> 19 Rad1 Radius.1 Rad
#> 28 Tib1 Tibia.1 Tib
#> 37 Uln1 Ulna.1 Ulna
#'
# Prepare statuaar_data_table
dl.tgb <- statuAAR::prep.statuaar.data(x, d.form = "wide", ind = "Appendix_row",
sex = "Sex", measures.names = "own", stats = FALSE)
#'
# Calculate stature estimation using a given formula.
statuAAR::getStature(c("ve09"), dl.tgb)
#> $ve09
#> sex stature bone if_female if_male if_indet n_measures
#> 1_1 m 1509 Fem1 1454 1509 1462 1
#> 1_10 m 1609 Fem1 1564 1609 1580 1
#> 1_11 m 1619 Fem1 1575 1619 1592 1
#> 1_12 m 1629 Fem1 1587 1629 1605 1
#> 1_13 m 1640 Fem1 1599 1640 1617 1
#> 1_14 m 1650 Fem1 1610 1650 1630 1
#> 1_15 m 1663 Fem1 1625 1663 1645 1
#> 1_16 m 1674 Fem1 1636 1674 1657 1
#> 1_17 m 1684 Fem1 1648 1684 1670 1
#> 1_18 m 1695 Fem1 1659 1695 1682 1
#> 1_19 m 1705 Fem1 1671 1705 1695 1
#> 1_2 m 1520 Fem1 1466 1520 1474 1
#> 1_20 m 1718 Fem1 1685 1718 1710 1
#> 1_21 m 1729 Fem1 1697 1729 1722 1
#> 1_22 m 1739 Fem1 1708 1739 1735 1
#> 1_23 m 1750 Fem1 1720 1750 1747 1
#> 1_24 m 1760 Fem1 1732 1760 1760 1
#> 1_25 m 1773 Fem1 1746 1773 1775 1
#> 1_26 m 1783 Fem1 1758 1783 1788 1
#> 1_27 m 1794 Fem1 1769 1794 1800 1
#> 1_28 m 1804 Fem1 1781 1804 1812 1
#> 1_29 m 1815 Fem1 1792 1815 1825 1
#> 1_3 m 1530 Fem1 1477 1530 1487 1
#> 1_30 m 1828 Fem1 1807 1828 1840 1
#> 1_31 m 1838 Fem1 1818 1838 1853 1
#> 1_32 m 1849 Fem1 1830 1849 1865 1
#> 1_33 m 1859 Fem1 1841 1859 1878 1
#> 1_34 m 1870 Fem1 1853 1870 1890 1
#> 1_35 m 1883 Fem1 1867 1883 1905 1
#> 1_36 m 1893 Fem1 1879 1893 1918 1
#> 1_37 m 1904 Fem1 1890 1904 1930 1
#> 1_38 m 1914 Fem1 1902 1914 1943 1
#> 1_39 m 1924 Fem1 1914 1924 1955 1
#> 1_4 m 1541 Fem1 1489 1541 1499 1
#> 1_40 m 1937 Fem1 1928 1937 1970 1
#> 1_41 m 1948 Fem1 1940 1948 1983 1
#> 1_42 m 1958 Fem1 1951 1958 1995 1
#> 1_43 m 1969 Fem1 1963 1969 2008 1
#> 1_44 m 1979 Fem1 1974 1979 2020 1
#> 1_45 m 1992 Fem1 1989 1992 2036 1
#> 1_46 m 2003 Fem1 2000 2003 2048 1
#> 1_47 m 2013 Fem1 2012 2013 2060 1
#> 1_5 m 1554 Fem1 1503 1554 1515 1
#> 1_6 m 1564 Fem1 1515 1564 1527 1
#> 1_7 m 1575 Fem1 1526 1575 1540 1
#> 1_8 m 1585 Fem1 1538 1585 1552 1
#> 1_9 m 1596 Fem1 1549 1596 1564 1
#> 3_1 f 1359 Fem1 1359 1423 1360 1
#> 3_10 f 1463 Fem1 1463 1517 1471 1
#> 3_11 f 1474 Fem1 1474 1528 1484 1
#> 3_12 f 1486 Fem1 1486 1538 1496 1
#> 3_13 f 1497 Fem1 1497 1549 1509 1
#> 3_14 f 1509 Fem1 1509 1559 1521 1
#> 3_15 f 1521 Fem1 1521 1569 1533 1
#> 3_16 f 1535 Fem1 1535 1582 1549 1
#> 3_17 f 1547 Fem1 1547 1593 1561 1
#> 3_18 f 1558 Fem1 1558 1603 1574 1
#> 3_19 f 1570 Fem1 1570 1614 1586 1
#> 3_2 f 1370 Fem1 1370 1434 1372 1
#> 3_20 f 1581 Fem1 1581 1624 1598 1
#> 3_21 f 1593 Fem1 1593 1635 1611 1
#> 3_22 f 1604 Fem1 1604 1645 1623 1
#> 3_23 f 1616 Fem1 1616 1656 1636 1
#> 3_24 f 1627 Fem1 1627 1666 1648 1
#> 3_25 f 1639 Fem1 1639 1676 1660 1
#> 3_26 f 1651 Fem1 1651 1687 1673 1
#> 3_27 f 1662 Fem1 1662 1697 1685 1
#> 3_28 f 1674 Fem1 1674 1708 1698 1
#> 3_29 f 1685 Fem1 1685 1718 1710 1
#> 3_3 f 1382 Fem1 1382 1444 1385 1
#> 3_30 f 1697 Fem1 1697 1729 1722 1
#> 3_31 f 1708 Fem1 1708 1739 1735 1
#> 3_32 f 1720 Fem1 1720 1750 1747 1
#> 3_33 f 1732 Fem1 1732 1760 1760 1
#> 3_34 f 1743 Fem1 1743 1770 1772 1
#> 3_35 f 1755 Fem1 1755 1781 1784 1
#> 3_36 f 1766 Fem1 1766 1791 1797 1
#> 3_37 f 1781 Fem1 1781 1804 1812 1
#> 3_38 f 1792 Fem1 1792 1815 1825 1
#> 3_39 f 1804 Fem1 1804 1825 1837 1
#> 3_4 f 1393 Fem1 1393 1455 1397 1
#> 3_40 f 1815 Fem1 1815 1836 1850 1
#> 3_41 f 1827 Fem1 1827 1846 1862 1
#> 3_42 f 1838 Fem1 1838 1857 1874 1
#> 3_43 f 1850 Fem1 1850 1867 1887 1
#> 3_44 f 1862 Fem1 1862 1877 1899 1
#> 3_45 f 1873 Fem1 1873 1888 1912 1
#> 3_5 f 1405 Fem1 1405 1465 1409 1
#> 3_6 f 1417 Fem1 1417 1475 1422 1
#> 3_7 f 1428 Fem1 1428 1486 1434 1
#> 3_8 f 1440 Fem1 1440 1496 1447 1
#> 3_9 f 1451 Fem1 1451 1507 1459 1
#>
# vercellotti_etal_2009(dl.tgb) # The alternative.