Sentence examples for reliability of agreement from inspiring English sources

Fleiss' kappa (named after Joseph L. Fleiss) is a statistical measure for assessing the reliability of agreement between a fixed number of raters when assigning categorical ratings to a number of items or classifying items.

Fleiss' kappa is another statistical measure for assessing the reliability of agreement between observers classifying a number of items.

Interobserver agreement was determined by Fleiss' kappa test [ 16], which is a statistical measure for assessing the reliability of agreement between more than 2 observers.

Fleiss' kappa assesses the reliability of agreement between a fixed number of raters/users (in this case 3) when assigning categorical ratings to a number of items or classifying items, in this case as foreground (liver) or background.

To determine the statistical reliability of agreement, we measured Cohen's kappa at the category level (0.80) and the subcategory level (0.74), with results that indicated a high level of agreement between coders.

One of the branches split genotypes B and C from the other genotypes and the other branch split genotypes A, B, and C from genotypes D and E. For example, when the segment size was 500 bp, the cluster of genotypes B and C had a relatively lower reliability of agreement (0.75 with 95% CI 0.74 - 0.76, Figure  4).

The conventional tests to evaluate random error include measures of reliability such as inter-rater reliability (tests of agreement between two independent raters) and tests of internal consistency (tests of the item correlations within parallel form scales).

These can be classified as inter-observer reliability (degree of agreement between different observers) and intra-observer or test-retest reliability (agreement between observations made by the same observer).

Each of the following code descriptions include the Krippendorff's (2011) alpha reliability statistics of agreement between the categories.

Figure  11a shows how reliability (proportion of agreement between the hand and automatic data processing) varies as a function of data quality.

A random sample of 20% of the responses was coded by a second rater, and inter-rater reliability of 90% agreement was achieved.