## What is a good Fleiss kappa?

This is the proportion of agreement over and above chance agreement. Fleiss’ kappa can range from -1 to +1….Interpreting the results from a Fleiss’ kappa analysis.

Value of κ | Strength of agreement |
---|---|

< 0.20 | Poor |

0.21-0.40 | Fair |

0.41-0.60 | Moderate |

0.61-0.80 | Good |

**How is Fleiss kappa calculated?**

Fleiss’ Kappa = (0.37802 – 0.2128) / (1 – 0.2128) = 0.2099. Although there is no formal way to interpret Fleiss’ Kappa, the following values show how to interpret Cohen’s Kappa, which is used to assess the level of inter-rater agreement between just two raters: < 0.20 | Poor.

### Why is my Kappa negative?

A negative kappa represents agreement worse than expected, or disagreement. Low negative values (0 to −0.10) may generally be interpreted as “no agreement”. A large negative kappa represents great disagreement among raters. Data collected under conditions of such disagreement among raters are not meaningful.

**What is the difference between Kappa and weighted kappa?**

Cohen’s kappa takes into account disagreement between the two raters, but not the degree of disagreement. The weighted kappa is calculated using a predefined table of weights which measure the degree of disagreement between the two raters, the higher the disagreement the higher the weight.

#### What does Fleiss mean?

Fleiss is a German surname meaning “diligence”.

**What is Fleiss Multirater Kappa?**

Fleiss’ multirater kappa (1971), which is a chance-adjusted index of agreement for multirater categorization of nominal variab.

## What is Fleiss kappa used for?

Fleiss’ Kappa is a way to measure agreement between three or more raters. It is recommended when you have Likert scale data or other closed-ended, ordinal scale or nominal scale (categorical) data.

**How is Cohen kappa calculated?**

Lastly, the formula for Cohen’s Kappa is the probability of agreement take away the probability of random agreement divided by 1 minus the probability of random agreement.

### What is weighted kappa?

Cohen’s weighted kappa is broadly used in cross-classification as a measure of agreement between observed raters. It is an appropriate index of agreement when ratings are nominal scales with no order structure.

**Is Fleiss kappa weighted?**

Cohen’s kappa is a measure of the agreement between two raters, where agreement due to chance is factored out. This extension is called Fleiss’ kappa. As for Cohen’s kappa no weighting is used and the categories are considered to be unordered.

#### What is weighted kappa used for?

**What is Fleiss formula?**

NFleiss = [1.96 sqrt(2*0.425*0.575)+0.842*sqrt(0.35*0.65+0.5*0.5)]2/(0.35-0.5)2=170. Therefore, using Fleiss’s formula 170 male and 170 female are required.

## What is Fleiss kappa in R?

Inter-Rater Reliability Measures in R The Fleiss kappa is an inter-rater agreement measure that extends the Cohen’s Kappa for evaluating the level of agreement between two or more raters, when the method of assessment is measured on a categorical scale.

**What are the alternatives to Fleiss kappa?**

Another alternative to the Fleiss Kappa is the Light’s kappa for computing inter-rater agreement index between multiple raters on categorical data. Light’s kappa is just the average Cohen’s Kappa (Chapter @ref (cohen-s-kappa)) if using more than 2 raters. Fleiss, J.L., and others. 1971.

### Is your study design Fleiss’ kappa-compliant?

Fleiss’ kappa is no exception. Therefore, you must make sure that your study design meets the basic requirements/assumptions of Fleiss’ kappa. If your study design does not meet these basic requirements/assumptions, Fleiss’ kappa is the incorrect statistical test to analyse your data.

**Is Fleiss’ kappa the wrong statistical test for your data?**

If your study design does not meet these basic requirements/assumptions, Fleiss’ kappa is the incorrect statistical test to analyse your data. However, there are often other statistical tests that can be used instead. Next, we set out the example we use to illustrate how to carry out Fleiss’ kappa using SPSS Statistics.