Calculate Scott's (1955) pi

spi() takes two vectors and returns Scott's (1955) pi coefficient, communicating extent of inter-observer reliability.

Usage

spi(x1, x2, levels = NULL)

Arguments

x1

a vector, and one assumes an integer

x2

a vector, and one assumes an integer

levels

defaults to NULL, but an optional vector that defines the full sequence of values that could be observed in x1 and x2. If NULL, the function looks for observed values.

Value

spi() takes two vectors and returns Scott's (1955) pi coefficient, communicating extent of inter-observer reliability.

Details

The function subsets to complete cases of the two vectors for which you want Scott's pi.

The function implicitly assumes that x1 and x2 are columns in a data frame. One indirect check for this looks at whether x1 and x2 are the same length. The function will stop if they're not.

There will sometimes be instances, assuredly with alliances, where not all categories are observed. For example, the toy example I provide of Germany and Russia in 1914 includes no 2s. In the language of "ratings", the "rating" of 2 was available for Germany and Russia in 1914 but neither side used it. The levels argument allows you to specify the full sequence of values that could be observed, even if none were. It probably makes the most sense to always use this argument, even if the default behavior operates as if you won't.

References

Scott, William A. 1955. "Reliability of Content Analysis: The Case of Nominal Scale Coding." Public Opinion Quarterly 19(3): 321–5.

Examples

spi(gmyrus14$gmy, gmyrus14$rus, levels = 0:3) # with levels argument
#> [1] -0.04477612
spi(usamex46$vote1, usamex46$vote2) # levels argument not necessary here.
#> [1] -0.02775801