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Calculate stature estimation according to: Vercellotti et al. 2009

Source: R/vercellotti_etal_2009.R
vercellotti_etal_2009.Rd

Stature 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

Usage

vercellotti_etal_2009(df)

Arguments

df

data.frame of type statuaar_data_table, containing informations on individual, bone and measurement.

Value

data.frame with calculated stature and related information per individual.

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 . https://onlinelibrary.wiley.com/doi/abs/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.
# Retrieve the first element of the list and display the first 6 lines.
statuAAR::getStature(c("ve09"), dl.tgb)[[1]] |> head(6)
#>      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
# vercellotti_etal_2009(dl.tgb) # The alternative.