diffTablej: calculates difference metrics at the category level from a square contingency table

Description

calculates quantity, exchange and shift components of difference, as well as the overall difference, at the category level from a contingency table derived from the crosstabulation between a comparison variable (or variable at time t), and a reference variable (or variable at time t+1).

Quantity difference is defined as the amount of difference between the reference variable and a comparison variable that is due to the less than maximum match in the proportions of the categories. Exchange consists of a transition from category i to category j in some observations and a transition from category j to category i in an identical number of other observations. Shift refers to the difference remaining after subtracting quantity difference and exchange from the overall difference.

Usage

diffTablej(ctmatrix, digits = 0, analysis = "error")

Value

data.frame containing difference metrics at the category level between a comparison variable (rows) and a reference variable (columns). Output values are given in the same units as ctmatrix

Arguments

ctmatrix: matrix representing a square contingency table between a comparison variable (rows) and a reference variable (columns)
digits: integer indicating the number of decimal places to be used
analysis: character string either "error" (default) or "change". The output table shows category-level omission error, agreement and comission error in the "error" analysis, and category-level gain, persistence and loss in the "change" analysis

References

Pontius Jr., R.G., Millones, M. 2011. Death to Kappa: birth of quantity disagreement and allocation disagreement for accuracy assessment. International Journal of Remote Sensing 32 (15), 4407-4429.

Pontius Jr., R.G., Santacruz, A. 2014. Quantity, exchange and shift components of difference in a square contingency table. International Journal of Remote Sensing 35 (21), 7543-7554.

Examples

Run this code

comp <- raster(system.file("external/comparison.rst", package="diffeR"))
ref <- raster(system.file("external/reference.rst", package="diffeR"))
ctmatCompRef <- crosstabm(comp, ref)
diffTablej(ctmatCompRef)

# Adjustment to population assumming a stratified random sampling
(population <- matrix(c(1,2,3,2000,4000,6000), ncol = 2))
ctmatCompRef <- crosstabm(comp, ref, percent = TRUE, population = population)
diffTablej(ctmatCompRef)