# rater.bias: Coefficient of rater bias In irr: Various Coefficients of Interrater Reliability and Agreement

## Description

Calculates a coefficient of systematic bias between two raters.

## Usage

 `1` ```rater.bias(x) ```

## Arguments

 `x` c x c classification matrix or 2 x n or n x 2 matrix of classification scores into c categories.

## Details

`rater.bias` calculates a reliability coefficient for two raters classifying n objects into any number of categories. It will accept either a c x c classification matrix of counts of objects falling into c categories or a 2 x n or n x 2 matrix of classification scores.
The function returns the absolute value of the triangular off-diagnonal sum ratio of the cxc classification table and the corresponding test statistic. A systematic bias between raters can be assumed when the ratio substantially deviates from 0.5 while yielding a significant Chi-squared statistic.

## Value

 `method` Name of the method `subjects` Number of subjects `raters` Number of raters (2) `irr.name` Name of the coefficient: ratio of triangular off-diagnonal sums `value` Value of the coefficient `stat.name` Name of the test statistic `statistic` Value of the test statistic `p.value` the probability of the df 1 Chi-square variable

Jim Lemon

## References

Bishop Y.M.M., Fienberg S.E., & Holland P.W. (1978). Discrete multivariate analysis: theory and practice. Cambridge, Massachusetts: MIT Press.

`mcnemar.test`

## Examples

 ```1 2 3 4 5 6 7``` ``` # fake a 2xn matrix of three way classification scores ratings <- matrix(sample(1:3,60,TRUE), nrow=2) rater.bias(ratings) # Example from Bishop, Fienberg & Holland (1978), Table 8.2-1 data(vision) rater.bias(vision) ```

### Example output

```Loading required package: lpSolve
Rater bias coefficient

Subjects = 30
Raters = 2
Ratio = 0.556

Chisq(1) = 0.222
p-value = 0.637
Rater bias coefficient

Subjects = 7477
Raters = 2
Ratio = 0.537

Chisq(1) = 11.9
p-value = 0.000566
```

irr documentation built on May 2, 2019, 8:50 a.m.