Calculate Cohen's (1960, 1968) weighted kappa
cohenk.Rdcohenk() takes two vectors and returns Cohen's kappa as an estimate
of chance-corrected agreement.
Arguments
- x1
a vector, and one assumes an integer
- x2
a vector, and one assumes an integer
- w_exp
an exponent to apply to the weight matrix. Default is 2 for squared distances in the weight matrix. Supplying a 1 would make for linear distances.
- levels
defaults to NULL, but an optional vector that defines the full sequence of values that could be observed in
x1andx2. If NULL, the function looks for observed values.
Value
cohenk() takes two vectors and returns Cohen's kappa as an estimate
of chance-corrected agreement.
Details
The function subsets to complete cases of the two vectors for which you want Cohen's kappa.
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.