Calculate interrater reliability using Cohen’s Kappa

Initial Program - Disposition

ELED

## Load the package
library(psych)
library(irr)
## Loading required package: lpSolve
library(Metrics)
## ELED
rater1 <- c(2,2,2,2,4,4,4,4,3,3,3,4,3,3,3,3) # rater one's ratings
rater2 <- c(3,3,3,3,4,3,4,3,2,4,3,3,3,3,3,4) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                    lower estimate upper
## unweighted kappa -0.1530   -0.032 0.089
## weighted kappa    0.0088    0.266 0.523
## 
##  Number of subjects = 16
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 16 
##    Raters = 2 
##     Kappa = -0.0323 
## 
##         z = -0.194 
##   p-value = 0.847
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0.266055
  • Unweighted kappa = - 0.032
  • Weighted kappa = 0.266
  • Quadratic Weighted Kappa = 0.266

SEEE

rater1 <- c(3,3,3,3) # rater one's ratings
rater2 <- c(3,3,3,3) # rater one's ratings
cohen.kappa(cbind(rater1,rater2)) 
## Your data seem to have no variance and in complete agreement across raters.  Check your data.
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa    NA       NA    NA
## weighted kappa     NaN      NaN   NaN
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = NaN 
## 
##         z = NaN 
##   p-value = NaN
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] NaN
  • Can not calculate because the complete agreement. Kappa=1

SESI

rater1 <- c(2,2,3,3) # rater one's ratings
rater2 <- c(3,3,3,3) # rater one's ratings
cohen.kappa(cbind(rater1,rater2))
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa     0        0     0
## weighted kappa       0        0     0
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = 0 
## 
##         z = NaN 
##   p-value = NaN
  • Kappa = 0 (No Z score and P-value because one of the rater only has 1 level)

HPPE

rater1 <- c(3,3,3,3) # rater one's ratings
rater2 <- c(3,3,3,3) # rater one's ratings
cohen.kappa(cbind(rater1,rater2))
## Your data seem to have no variance and in complete agreement across raters.  Check your data.
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa    NA       NA    NA
## weighted kappa     NaN      NaN   NaN
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = NaN 
## 
##         z = NaN 
##   p-value = NaN
  • Can not calculate because the complete agreement. Kappa=1

SELA

rater1 <- c(3,4,3,3) # rater one's ratings
rater2 <- c(3,3,3,3) # rater one's ratings
cohen.kappa(cbind(rater1,rater2))
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa     0        0     0
## weighted kappa       0        0     0
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = 0 
## 
##         z = NaN 
##   p-value = NaN
  • Kappa = 0 (No Z score and P-value because one of the rater only has 1 level)

SPCO

rater1 <- c(3,4,3,4) # rater one's ratings
rater2 <- c(4,3,4,3) # rater one's ratings
cohen.kappa(cbind(rater1,rater2))
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa    -1       -1    -1
## weighted kappa      -1       -1    -1
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = -1 
## 
##         z = -2 
##   p-value = 0.0455
  • Kappa=-1, Totally disagreement.

SESS

rater1 <- c(3,2,2,2) # rater one's ratings
rater2 <- c(2,3,2,3) # rater one's ratings
cohen.kappa(cbind(rater1,rater2))
## Warning in cohen.kappa1(x, w = w, n.obs = n.obs, alpha = alpha, levels =
## levels): upper or lower confidence interval exceed abs(1) and set to +/- 1.
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa    -1     -0.5  0.23
## weighted kappa      -1     -0.5  0.23
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = -0.5 
## 
##         z = -1.15 
##   p-value = 0.248
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] -0.5
  • Unweighted kappa = -0.5
  • Weighted kappa = -0.5
  • Quadratic Weighted Kappa = -0.5

Initial Program - Portfolio

ELED

rater1 <- c(2,2,2,2,2,2,3,4,3,4,2,2,3,4,3,4,4,3,3,3,3,3,3,3) # rater one's ratings
rater2 <- c(3,3,4,3,3,2,4,4,4,4,4,4,4,3,3,4,3,3,3,3,4,4,3,3) # rater one's ratings
cohen.kappa(cbind(rater1,rater2))
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa -0.14     0.12  0.38
## weighted kappa   -0.33     0.16  0.65
## 
##  Number of subjects = 24
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 24 
##    Raters = 2 
##     Kappa = 0.118 
## 
##         z = 0.943 
##   p-value = 0.346
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0.1636364
  • Unweighted kappa = 0.12
  • weighted kappa = 0.16
  • Quadratic Weighted Kappa = 0.16

SEEE

rater1 <- c(3,3,3,3,3,3) # rater one's ratings
rater2 <- c(3,3,3,3,2,3) # rater one's ratings
cohen.kappa(cbind(rater1,rater2))
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                     lower estimate   upper
## unweighted kappa -1.3e-07        0 1.3e-07
## weighted kappa   -1.2e-07        0 1.2e-07
## 
##  Number of subjects = 6
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 6 
##    Raters = 2 
##     Kappa = 0 
## 
##         z = 0 
##   p-value = 1
  • Kappa = 0 (one of the rater only has 1 level)

SESI

rater1 <- c(2,3,3,3,3,2) # rater one's ratings
rater2 <- c(3,3,3,3,3,3) # rater one's ratings
cohen.kappa(cbind(rater1,rater2))
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa     0        0     0
## weighted kappa       0        0     0
## 
##  Number of subjects = 6
kappa2(cbind(rater1,rater2))
## Warning in sqrt(varkappa): NaNs produced
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 6 
##    Raters = 2 
##     Kappa = 0 
## 
##         z = NaN 
##   p-value = NaN
  • Kappa = 0 (No Z score and P-value because one of the rater only has 1 level)

HPPE

rater1 <- c(3,3,3,3,4,3) # rater one's ratings
rater2 <- c(3,3,3,3,3,3) # rater one's ratings
cohen.kappa(cbind(rater1,rater2))
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                     lower estimate   upper
## unweighted kappa -1.3e-07        0 1.3e-07
## weighted kappa   -1.2e-07        0 1.2e-07
## 
##  Number of subjects = 6
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 6 
##    Raters = 2 
##     Kappa = 0 
## 
##         z = 0 
##   p-value = 1
  • Kappa = 0 (one of the rater only has 1 level)

SELA

rater1 <- c(3,3,3,3,3,3) # rater one's ratings
rater2 <- c(3,3,3,3,3,3) # rater one's ratings
cohen.kappa(cbind(rater1,rater2))
## Your data seem to have no variance and in complete agreement across raters.  Check your data.
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa    NA       NA    NA
## weighted kappa     NaN      NaN   NaN
## 
##  Number of subjects = 6
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 6 
##    Raters = 2 
##     Kappa = NaN 
## 
##         z = NaN 
##   p-value = NaN
  • Can not calculate because the complete agreement. Kappa=1

SPCO

rater1 <- c(4,4,3,3,4,3) # rater one's ratings
rater2 <- c(4,3,4,4,3,3) # rater one's ratings
cohen.kappa(cbind(rater1,rater2))
## Warning in cohen.kappa1(x, w = w, n.obs = n.obs, alpha = alpha, levels =
## levels): upper or lower confidence interval exceed abs(1) and set to +/- 1.
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa    -1    -0.33  0.42
## weighted kappa      -1    -0.33  0.42
## 
##  Number of subjects = 6
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 6 
##    Raters = 2 
##     Kappa = -0.333 
## 
##         z = -0.816 
##   p-value = 0.414
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] -0.3333333
  • Unweighted kappa = -0.33
  • Weighted kappa = -0.33
  • Quadratic Weighted Kappa = -0.33

SESS

rater1 <- c(2,2,3,3,2,1) # rater one's ratings
rater2 <- c(3,3,2,2,3,2) # rater one's ratings
cohen.kappa(cbind(rater1,rater2))
## Warning in cohen.kappa1(x, w = w, n.obs = n.obs, alpha = alpha, levels =
## levels): upper or lower confidence interval exceed abs(1) and set to +/- 1.
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa    -1    -0.71 -0.32
## weighted kappa      -1    -0.20  1.00
## 
##  Number of subjects = 6
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 6 
##    Raters = 2 
##     Kappa = -0.714 
## 
##         z = -2.27 
##   p-value = 0.0229
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] -0.2
  • Unweighted kappa = -0.71
  • Weighted kappa = -0.20
  • Quadratic Weighted Kappa = -0.20

MA Level - Disposition

COED

rater1 <- c(3,4,3,4) # rater one's ratings
rater2 <- c(3,3,4,3) # rater one's ratings
cohen.kappa(cbind(rater1,rater2))
## Warning in cohen.kappa1(x, w = w, n.obs = n.obs, alpha = alpha, levels =
## levels): upper or lower confidence interval exceed abs(1) and set to +/- 1.
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa    -1     -0.5  0.23
## weighted kappa      -1     -0.5  0.23
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = -0.5 
## 
##         z = -1.15 
##   p-value = 0.248
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] -0.5
  • Unweighted kappa = -0.5
  • Weighted kappa = -0.5
  • Quadratic Weighted Kappa = -0.5

ELED

rater1 <- c(3,3,3,3) # rater one's ratings
rater2 <- c(3,2,3,2) # rater one's ratings
cohen.kappa(cbind(rater1,rater2))
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa     0        0     0
## weighted kappa       0        0     0
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = 0 
## 
##         z = NaN 
##   p-value = NaN
  • Kappa = 0 (one of the rater only has 1 level)

SPGT

rater1 <- c(4,3,3,4) # rater one's ratings
rater2 <- c(3,3,3,3) # rater one's ratings
cohen.kappa(cbind(rater1,rater2))
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa     0        0     0
## weighted kappa       0        0     0
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = 0 
## 
##         z = NaN 
##   p-value = NaN
  • Kappa = 0 (one of the rater only has 1 level)

EDLE

rater1 <- c(3,3,3,3) # rater one's ratings
rater2 <- c(3,3,3,3) # rater one's ratings
cohen.kappa(cbind(rater1,rater2))
## Your data seem to have no variance and in complete agreement across raters.  Check your data.
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa    NA       NA    NA
## weighted kappa     NaN      NaN   NaN
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = NaN 
## 
##         z = NaN 
##   p-value = NaN
  • Can not calculate because the complete agreement. Kappa=1

SPCO

rater1 <- c(4,3,3,3) # rater one's ratings
rater2 <- c(4,3,3,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa     1        1     1
## weighted kappa       1        1     1
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = 1 
## 
##         z = 2 
##   p-value = 0.0455
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 1
  • Kappa=1

EDSY

rater1 <- c(4,4,4,4) # rater one's ratings
rater2 <- c(4,4,3,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa     0        0     0
## weighted kappa       0        0     0
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = 0 
## 
##         z = NaN 
##   p-value = NaN
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0
  • Kappa = 0 (one of the rater only has 1 level)

MA Level - Portfolio

COED

rater1 <- c(3,3,3,3,4,4) # rater one's ratings
rater2 <- c(3,3,3,3,3,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa     0        0     0
## weighted kappa       0        0     0
## 
##  Number of subjects = 6
kappa2(cbind(rater1,rater2))
## Warning in sqrt(varkappa): NaNs produced
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 6 
##    Raters = 2 
##     Kappa = 0 
## 
##         z = NaN 
##   p-value = NaN
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0
  • Kappa = 0 (one of the rater only has 1 level)

ELED

rater1 <- c(4,3,4,3,3,4) # rater one's ratings
rater2 <- c(2,3,2,2,3,2) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate   upper
## unweighted kappa  0.13     0.20  0.2697
## weighted kappa   -0.36    -0.18 -0.0018
## 
##  Number of subjects = 6
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 6 
##    Raters = 2 
##     Kappa = 0.2 
## 
##         z = 1.73 
##   p-value = 0.0833
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] -0.1818182
  • Unweighted kappa = 0.20
  • Weighted kappa = -0.182
  • Quadratic Weighted Kappa = -0.182

SPGT

rater1 <- c(3,4,3,4,4,4) # rater one's ratings
rater2 <- c(3,3,3,3,3,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa     0        0     0
## weighted kappa       0        0     0
## 
##  Number of subjects = 6
kappa2(cbind(rater1,rater2))
## Warning in sqrt(varkappa): NaNs produced
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 6 
##    Raters = 2 
##     Kappa = 0 
## 
##         z = NaN 
##   p-value = NaN
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0
  • Kappa = 0 (one of the rater only has 1 level)

EDLE

rater1 <- c(3,3,3,3,2,3) # rater one's ratings
rater2 <- c(3,3,3,3,3,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                     lower estimate   upper
## unweighted kappa -4.5e-08        0 4.5e-08
## weighted kappa   -4.1e-08        0 4.1e-08
## 
##  Number of subjects = 6
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 6 
##    Raters = 2 
##     Kappa = 0 
## 
##         z = 0 
##   p-value = 1
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0
  • Kappa = 0 (one of the rater only has 1 level)

SPCO

rater1 <- c(3,3,3,3,4,3) # rater one's ratings
rater2 <- c(3,3,3,3,4,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Warning in cohen.kappa1(x, w = w, n.obs = n.obs, alpha = alpha, levels =
## levels): upper or lower confidence interval exceed abs(1) and set to +/- 1.
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa     1        1     1
## weighted kappa       1        1     1
## 
##  Number of subjects = 6
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 6 
##    Raters = 2 
##     Kappa = 1 
## 
##         z = 2.45 
##   p-value = 0.0143
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 1
  • Can not calculate because the complete agreement. Kappa=1

EDSY

rater1 <- c(3,4,3,3,4,4) # rater one's ratings
rater2 <- c(3,3,4,3,4,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa -0.26        0  0.26
## weighted kappa   -0.26        0  0.26
## 
##  Number of subjects = 6
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 6 
##    Raters = 2 
##     Kappa = 0 
## 
##         z = 0 
##   p-value = 1
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0
  • Unweighted kappa = 0
  • Weighted kappa = 0
  • Quadratic Weighted Kappa = 0

EDS - Disposition

EDSP

rater1 <- c(2,2,3,2) # rater one's ratings
rater2 <- c(3,4,4,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate  upper
## unweighted kappa -0.22    -0.14 -0.065
## weighted kappa    0.12     0.12  0.125
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = -0.143 
## 
##         z = -1.15 
##   p-value = 0.248
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0.125
  • Unweighted kappa - 0.14
  • Weighted kappa = 0.125
  • Quadratic Weighted Kappa = 0.125

EDLE

rater1 <- c(3,3,3,3) # rater one's ratings
rater2 <- c(3,3,3,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Your data seem to have no variance and in complete agreement across raters.  Check your data.
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa    NA       NA    NA
## weighted kappa     NaN      NaN   NaN
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = NaN 
## 
##         z = NaN 
##   p-value = NaN
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] NaN
  • Can not calculate because the complete agreement. Kappa=1

ELED

rater1 <- c(2,1,2,2) # rater one's ratings
rater2 <- c(4,4,4,4) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa     0        0     0
## weighted kappa       0        0     0
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = 0 
## 
##         z = NaN 
##   p-value = NaN
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0
  • Kappa = 0 (one of the rater only has 1 level)

COED

rater1 <- c(4,4,4,4) # rater one's ratings
rater2 <- c(3,3,3,2) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa     0        0     0
## weighted kappa       0        0     0
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = 0 
## 
##         z = NaN 
##   p-value = NaN
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0
  • Kappa = 0 (one of the rater only has 1 level)

EDS - Portfolio

EDSP

rater1 <- c(3,2,2,2,3,2) # rater one's ratings
rater2 <- c(3,3,3,3,4,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate  upper
## unweighted kappa -0.24    -0.15 -0.071
## weighted kappa    0.21     0.21  0.211
## 
##  Number of subjects = 6
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 6 
##    Raters = 2 
##     Kappa = -0.154 
## 
##         z = -1.55 
##   p-value = 0.121
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0.2105263
  • Unweighted kappa = -0.15
  • Weighted kappa = 0.211
  • Quadratic Weighted Kappa = 0.211

EDLE

rater1 <- c(3,3,3,3,3,3) # rater one's ratings
rater2 <- c(3,3,3,3,3,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Your data seem to have no variance and in complete agreement across raters.  Check your data.
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa    NA       NA    NA
## weighted kappa     NaN      NaN   NaN
## 
##  Number of subjects = 6
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 6 
##    Raters = 2 
##     Kappa = NaN 
## 
##         z = NaN 
##   p-value = NaN
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] NaN
  • Can not calculate because the complete agreement. Kappa=1

ELED

rater1 <- c(2,2,2,2,2,1) # rater one's ratings
rater2 <- c(4,4,4,4,3,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa  0.00     0.00  0.00
## weighted kappa    0.06     0.06  0.06
## 
##  Number of subjects = 6
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 6 
##    Raters = 2 
##     Kappa = 0 
## 
##         z = NaN 
##   p-value = NaN
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0.05970149
  • Unweighted kappa = 0
  • Weighted kappa = 0.06
  • Quadratic Weighted Kappa = 0.059

COED

rater1 <- c(4,4,3,4,4,3) # rater one's ratings
rater2 <- c(3,3,3,4,4,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa  0.21      0.4  0.59
## weighted kappa    0.21      0.4  0.59
## 
##  Number of subjects = 6
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 6 
##    Raters = 2 
##     Kappa = 0.4 
## 
##         z = 1.22 
##   p-value = 0.221
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0.4
  • Unweighted kappa = 0.4
  • Weighted kappa = 0.4
  • Quadratic Weighted Kappa = 0.4

Standards for Initial ELED - Dispositions

Standard 1 - Diversity

rater1 <- c(2,4,3,3) # rater one's ratings
rater2 <- c(3,4,2,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa -0.08      0.2  0.48
## weighted kappa    0.19      0.5  0.81
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = 0.2 
## 
##         z = 0.555 
##   p-value = 0.579
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0.5
  • Unweighted kappa = 0.2
  • Quadratic Weighted Kappa = 0.5

Standard 2 - Fairness and Equity

rater1 <- c(2,4,3,3) # rater one's ratings
rater2 <- c(3,3,4,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Warning in cohen.kappa1(x, w = w, n.obs = n.obs, alpha = alpha, levels =
## levels): upper or lower confidence interval exceed abs(1) and set to +/- 1.
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa  -0.5    -0.33 -0.17
## weighted kappa    -1.0     0.00  1.00
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = -0.333 
## 
##         z = -1.04 
##   p-value = 0.296
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0
  • Unweighted kappa = -0.33
  • Quadratic Weighted Kappa = 0

Standard 3 - Collaboration

rater1 <- c(2,4,3,3) # rater one's ratings
rater2 <- c(3,4,3,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa  0.34     0.56  0.77
## weighted kappa    0.67     0.67  0.67
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = 0.556 
## 
##         z = 1.74 
##   p-value = 0.0817
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0.6666667
  • Unweighted kappa = 0.56
  • Quadratic Weighted Kappa = 0.667

Standard 4 - Reflective Practice

rater1 <- c(2,4,4,3) # rater one's ratings
rater2 <- c(3,3,3,4) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa -0.72    -0.45 -0.19
## weighted kappa   -0.14    -0.14 -0.14
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = -0.455 
## 
##         z = -1.74 
##   p-value = 0.0817
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] -0.1428571
  • Unweighted kappa = -0.45
  • Quadratic Weighted Kappa = -0.14

Standards for Initial ELED - Portfolio

Standard 1 - The Learner and Learning

rater1 <- c(2,3,3,3) # rater one's ratings
rater2 <- c(3,4,4,4) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                   lower estimate upper
## unweighted kappa -0.341    -0.23 -0.12
## weighted kappa   -0.064     0.27  0.61
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = -0.231 
## 
##         z = -2 
##   p-value = 0.0455
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0.2727273
  • Unweighted kappa = -0.23
  • Quadratic Weighted Kappa = 0.27

Standard 2 - Learning Environments

rater1 <- c(2,4,4,3) # rater one's ratings
rater2 <- c(3,4,3,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa  0.11     0.27  0.44
## weighted kappa    0.32     0.43  0.54
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = 0.273 
## 
##         z = 1.04 
##   p-value = 0.296
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0.4285714
  • Unweighted kappa = 0.27
  • Quadratic Weighted Kappa = 0.43

Standard 3 - Content Knowledge

rater1 <- c(2,3,3,3) # rater one's ratings
rater2 <- c(4,4,3,4) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa  0.02    0.077  0.13
## weighted kappa   -0.63   -0.091  0.45
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = 0.0769 
## 
##         z = 0.667 
##   p-value = 0.505
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] -0.09090909
  • Unweighted kappa = 0.077
  • Quadratic Weighted Kappa = -0.091

Standard 4 - Instructional Practice

rater1 <- c(2,4,4,3) # rater one's ratings
rater2 <- c(3,4,4,4) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                   lower estimate upper
## unweighted kappa -0.026     0.11  0.25
## weighted kappa    0.518     0.56  0.59
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = 0.111 
## 
##         z = 0.348 
##   p-value = 0.728
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0.5555556
  • Unweighted kappa = 0.11
  • Quadratic Weighted Kappa = 0.56

Standard 5 - Professional Learning and Ethical Practice

rater1 <- c(2,2,4,3) # rater one's ratings
rater2 <- c(3,4,3,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                   lower estimate  upper
## unweighted kappa -0.079     0.00  0.079
## weighted kappa   -0.333    -0.33 -0.333
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = 0 
## 
##         z = 0 
##   p-value = 1
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] -0.3333333
  • Unweighted kappa = 0
  • Quadratic Weighted Kappa = -0.33

Standard 6 - Leadership and Collaboration

rater1 <- c(2,2,3,3) # rater one's ratings
rater2 <- c(2,4,3,3) # rater one's ratings
cohen.kappa(x=cbind(rater1,rater2),alpha=.5)
## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
## 
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries 
##                  lower estimate upper
## unweighted kappa  0.43      0.6  0.77
## weighted kappa   -0.65      0.0  0.65
## 
##  Number of subjects = 4
kappa2(cbind(rater1,rater2))
##  Cohen's Kappa for 2 Raters (Weights: unweighted)
## 
##  Subjects = 4 
##    Raters = 2 
##     Kappa = 0.6 
## 
##         z = 1.81 
##   p-value = 0.0704
ScoreQuadraticWeightedKappa(rater1,rater2)
## [1] 0
  • Unweighted kappa = 0.6
  • Quadratic Weighted Kappa = 0