SalienceContrastPlot: SalienceContrastPlot

In alastair-JL/AnthroTools: Some custom tools for anthropology

SalienceContrastPlot

Description

Plotting function to generate density plots of contrasts in Smith's S estimates over a range of items. The input to this function is the output of the 'SalienceContrastGen()' command; i.e., a list of vectors of Smith's S contrasts between items. Note that this command relies on the 'tidyverse', 'ggplot2' and 'ggdist' packages - Make sure that these are installed and loaded.

Usage

SalienceContrastPlot(data, target, order = "high-low", manual_order)

Arguments

data	This is a list of vectors of contrasts in Smith's S estimates (i.e., the output of the 'SalienceContrastGen()' command).
target	The baseline item level to compare contrasts against.
order	String to denote the order in which to display items on the plot. Options are: "high-low" (from highest to lowest; the default), "low-high" (from lowest to highest), "alpha" (alphabetically), and "manual" (manually specify order - see 'manual_order' option).
manual_order	A vector of variable names specifying the order in which to display items on the plot. Only to be used if 'order = "manual"' (else this option is ignored).

Value

A series of distributions for each item contrast by Smith's S estimates, along with 80

Author(s)

Daniel Major-Smith. <[e-mail]>

Benjamin Grant Purzycki. <[e-mail]>

Examples

## Generate fake free-list data about fruits
set.seed(41)
fakeData <- GenerateFakeFreeListData() 

## Calculate item salience
fakeData.s <- CalculateSalience(fakeData, Subj = "Subj", Order = "Order", 
		CODE = "CODE", Salience = "CODE.S")

## Convert to data frame with maximum item saliences for each item as 
## separate rows, and including 0s
fakeData.sal0 <- FreeListTable(fakeData.s, Subj = "Subj", Order = "Order", 
		CODE = "CODE", Salience = "CODE.S", tableType = "MAX_SALIENCE")
head(fakeData.sal0)

## Calculate uncertainty in Smith's S via boot-strapping for top 6 items 
## in terms of Smith's S, using 1,000 iterations for each item
S_boot <- SalienceBoot(fakeData.sal0, var_sel = "TOP", top = 6, 
		iterations = 1000, seed = 182, IDs_first = TRUE)

## Contrasts between each item (on absolute difference scale)
S_contrasts <- SalienceContrastGen(S_boot, contrast = "absolute_diff")

## Plot of these results
# Ranked from highest to lowest
SalienceContrastPlot(data = S_contrasts, target = "apple", order = "high-low")

# And using manual specification
SalienceContrastPlot(data = S_contrasts, target = "apple", order = "manual", 
		manual_order = c("banana", "orange", "pear", "plum", "peach"))

alastair-JL/AnthroTools documentation built on June 10, 2025, 3:08 p.m.