Pottery2: Chemical Analysis of Romano-British Pottery

Description

Results of chemical analyses of 48 specimens of Romano-British pottery published by Tubb et al. (1980). The numbers are the percentage of various metal oxides found in each sample for elements of concentrations greater than 0.01%. This is the original data set from Tubb et al. (1980), in contrast to Pottery.

Arguments

Format

A data frame with 48 observations on the following 12 variables.

Region: a factor with levels Gl NF Wales
Site: a factor with levels AshleyRails Caldicot Gloucester IsleThorns Llanedryn
Kiln: a factor with levels 1 2 3 4 5
Al: amount of aluminum oxide, \(Al_2O_3\)
Fe: amount of iron oxide, \(Fe_2O_3\)
Mg: amount of magnesium oxide, MgO
Ca: amount of calcium oxide, CaO
Na: amount of sodium oxide, \(Na_2O\)
K: amount of potassium oxide, \(K_2O\)
Ti: amount of titanium oxide, \(TiO_2\)
Mn: amount of manganese oxide, MnO
Ba: amount of BaO

Details

The specimens are identified by their rownames in the data frame. Kiln indicates at which kiln site the pottery was found; Site gives the location names of those sites. The kiln sites come from three Regions, ("Gl"=1, "Wales"=(2, 3), "NF"=(4, 5)), where the full names are "Gloucester", "Wales", and "New Forrest".

The variable Kiln comes pre-supplied with contrasts to test interesting hypotheses related to Site and Region.

References

Baxter, M. J. 2003. Statistics in Archaeology. Arnold, London.

Carlson, David L. 2017. Quantitative Methods in Archaeology Using R. Cambridge University Press, pp 247-255, 335-342.

Tubb, A., A. J. Parker, and G. Nickless. 1980. The Analysis of Romano-British Pottery by Atomic Absorption Spectrophotometry. Archaeometry, 22, 153-171.

Examples

Run this code


library(car)
data(Pottery2)
# contrasts for Kiln correspond to between Region [,1:2] and within Region [,3:4]
contrasts(Pottery2$Kiln)

pmod <-lm(cbind(Al,Fe,Mg,Ca,Na,K,Ti,Mn,Ba)~Kiln, data=Pottery2)
car::Anova(pmod)

# extract coefficient names for linearHypotheses
coefs <- rownames(coef(pmod))[-1]

# test differences among regions
linearHypothesis(pmod, coefs[1:2])
# test differences within regions B, C
linearHypothesis(pmod, coefs[3:4])

heplot(pmod, fill=c(TRUE,FALSE), hypotheses=list("Region" =coefs[1:2], "WithinBC"=coefs[3:4]))

# all pairwise views;  note that Ba shows no effect
pairs(pmod, fill=c(TRUE,FALSE))

# canonical view, via candisc::heplot

if (require(candisc)) {

# canonical analysis: how many dimensions?
(pcan <- candisc(pmod))

heplot(pcan, scale=18, fill=c(TRUE,FALSE), var.col="darkgreen", var.lwd=2, var.cex=1.5)

if (FALSE) {
heplot3d(pcan, scale=8)
}
}