Cohen´s Kappa

This paper aims to estimate intercoder reliability in content analysis of international online media. In order to measure this rate of agreement, we have selected three of the twenty-five online media that configure the corpus of the research: The Guardian, Clarín and Asahi Shimbun. The English Web Edition. We make use of two types of indexes. On the one hand, Holsti's liberal method; and on the other hand, Cohen's Kappa, a conservative index. The study is part of the research project "Evolution of the online media in the context of convergence: message analysis" (CSO2009-13713-C05-04-sub-SOCI-).

[Contenido en castellano]. La Kappa (Cohen, 1960) es un índice estadístico que mide el acuerdo entre las evaluaciones o diagnósticos de dos jueces, evaluadores o investigadores siempre y cuando estén evaluando lo mismo con los mismos criterios. Además, es imprescindible que los evaluadores trabajen con la misma variable cualitativa nominal.

The question of data reliability is of first importance to assess the quality of manually annotated corpora. Although Cohen ' s κ is the prevailing reliability measure used in NLP, alternative statistics have been proposed. This paper presents an experimental study with four measures (Cohen's κ, Scott's π, binary and weighted Krippendorff ' s α) on three tasks: emotion, opinion and coreference annotation. The reported studies investigate the factors of influence (annotator bias, category prevalence, number of coders, number of categories) that should affect reliability estimation. Results show that the use of a weighted measure restricts this influence on ordinal annotations. They suggest that weighted α is the most reliable metrics for such an annotation scheme.

Objective: To run logistic regression after merging two variables of raters depending on percent of agreement. Methodology: Percent of agreement identifies quantitative expression of observer variation between two raters. Correct identification of abnormal and normal subjects depends on terms of sensitivity
and specificity. Merging of two variables to have one variable is a crucial step to identify the only diseased/abnormal subjects by two raters. Thereby, logistic regression takes place to evaluate whether risk factors are associated with a defined condition. Conclusion: Using of statistical agreement to run logistic regression can help researchers to assess strong risk factors for one disease diagnosed and agreement by two
raters for the same subjects by one step.

The author has developed a general theory for measuring the statistical interconnections between events, called ``mathematical eventology'' \cite[2007]{Vorobyev2007}, \cite[2011]{Vorobyev2011em}. The paper represents fresh ``eventological'' ideas that radically rethinking the basis of previous approaches to measuring statistical interconnections of events beyond the traditional measurements in the probability theory and mathematical statistics, adding to the already well-known  methods of measuring association, or statistical dependency, another new group of methods of measuring agreement of a set of events.
It shows by useful ``total'' quantities (called agreement, association, covariance, set-distance, set-nearness, and set-closeness of a set of events) formulas in this context can be simplified and elegantly summarized for many applications, including for the correct generalization of the traditional indicators of statistical interconnections of events as Pearson correlation, Yule association, as well as a popular index of agreement --- Cohen kappa \cite[1960]{Cohen1960}.
Proposed new methods demonstrate the growing potential of ``eventological'' technologies in the study of structures of interconnections (agreement, association, or statistical dependency) of events, which applies to the measurement in the nominal (categorical), and the ordered and numeric (difference, ratio) scales.
The development and use in a variety of applications of the new concept of the set-distance for a set of events must have necessarily come into contact with the area of modern multivariate statistics that deals with measuring the commonality (agreement) of experts in estimates within categorical (nominal) scales. The results of this dramatic contact are set forth below. As the ``whipping boy'', the most popular group of such statistics is chosen: the kappa-indicators of the commonality (agreement) of experts in estimates within categorical scales.

Both empirical and mathematical demonstrations of the importance of chance-corrected measures are discussed, and a new model of learning is proposed based on empirical psychological results on association learning. Two forms of this model are developed, the Informatron as a chance-corrected Perceptron, and AdaBook as a chance-corrected AdaBoost procedure. Computational results presented show chance correction facilitates learning.

Stack Overflow is the most popular Q&A website which is used by developers and programmers for many developments and programming purposes. Stack Overflow commits occur based on various types of programming languages. But among all the languages which are more reliable and helpful for programmers is a burning question. We researched over Stack Overflow commits and reached in a conclusion. Our main target was to analyze over Stack Overflow commits and to give a result which can raise the confidence level of a programmer. In this research, we will show which language and platform are better for developers and programmers. We used 1139 Stack Overflow related commits, analyzed them and came to an end that in "JavaScript" language programmers involve most and in "Java", response time is less than other languages. We also found that in "Python", programmers have a large probability to get an answer. We also analyzed different platforms in Stack Overflow and fo...

Objective:
Self-reported information from questionnaires is frequently used in epidemiological studies, but few of these studies provide information on the reproducibility of individual items contained in the questionnaire. We studied the test–retest reliability of self-reported diabetes among 33,919 participants in Norwegian Women and Cancer Study.

Methods:
The test–retest reliability of self-reported type 1 and type 2 diabetes diagnoses was evaluated between three self-administered questionnaires (completed in 1991, 1998, and 2005 by Norwegian Women and Cancer participants) by kappa agreement. The time interval between the test–retest studies was ~7 and ~14 years. Sensitivity of the kappa agreement for type 1 and type 2 diabetes diagnoses was assessed. Subgroup analysis was performed to assess whether test–retest reliability varies with age, body mass index, physical activity, education, and smoking status.

Results:
The kappa agreement for both types of self-reported diabetes diagnoses combined was good (⩾0.65) for all three test–retest studies (1991–1998, 1991–2005, and 1998–2005). The kappa agreement for type 1 diabetes was good (⩾0.73) in the 1991–2005 and the 1998–2005 test–retest studies, and very good (0.83) in the 1991–1998 test–retest study. The kappa agreement for type 2 diabetes was moderate (0.57) in the 1991–2005 test–retest study and good (⩾0.66) in the 1991–1998 and 1998–2005 test–retest studies. The overall kappa agreement in the 1991–1998 test–retest study was stronger than in the 1991–2005 test–retest study and the 1998–2005 test–retest study. There was no clear pattern of inconsistency in the kappa agreements within different strata of age, BMI, physical activity, and smoking. The kappa agreement was strongest among the respondents with 17 or more years of education, while generally it was weaker among the least educated group.

Conclusion:
The test–retest reliability of the diabetes was acceptable and there was no clear pattern of inconsistency in the kappa agreement stratified by age, body mass index, physical activity, and smoking. The study suggests that self-reported diabetes diagnosis from middle-aged women enrolled in the Norwegian Women and Cancer Study is reliable.

Evaluation often aims to reduce the correctness or error characteristics of a system down to a single number, but that always involves trade-offs. Another way of dealing with this is to quote two numbers, such as Recall and Precision, or Sensitivity and Specificity. But it can also be useful to see more than this, and a graphical approach can explore sensitivity to cost, prevalence, bias, noise, parameters and hyper-parameters.

Moreover, most techniques are implicitly based on two balanced classes, and our ability to visualize graphically is intrinsically two dimensional, but we often want to visualize in a multiclass context. We review the dichotomous approaches relating to Precision, Recall, and ROC as well as the related LIFT chart, exploring how they handle unbalanced and multiclass data, and deriving new probabilistic and information theoretic variants of LIFT that help deal with the issues associated with the handling of multiple and unbalanced classes.

It is becoming clear that traditional
evaluation measures used in
Computational Linguistics (including
Error Rates, Accuracy, Recall, Precision
and F-measure) are of limited value for
unbiased evaluation of systems, and are
not meaningful for comparison of
algorithms unless both the dataset and
algorithm parameters are strictly
controlled for skew (Prevalence and
Bias). The use of techniques originally
designed for other purposes, in particular
Receiver Operating Characteristics Area
Under Curve, plus variants of Kappa,
have been proposed to fill the void.
This paper aims to clear up some of the
confusion relating to evaluation, by
demonstrating that the usefulness of each
evaluation method is highly dependent on
the assumptions made about the
distributions of the dataset and the
underlying populations. The behaviour of
a number of evaluation measures is
compared under common assumptions.
Deploying a system in a context which
has the opposite skew from its validation
set can be expected to approximately
negate Fleiss Kappa and halve Cohen
Kappa but leave Powers Kappa
unchanged. For most performance
evaluation purposes, the latter is thus
most appropriate, whilst for comparison
of behaviour, Matthews Correlation is
recommended.

Stack Overflow is the most popular Q&A website which is used by developers and programmers for many developments and programming purposes. Stack Overflow commits occur based on various types of programming languages. But among all the languages which are more reliable and helpful for programmers is a burning question. We researched over Stack Overflow commits and reached in a conclusion. Our main target was to analyze over Stack Overflow commits and to give a result which can raise the confidence level of a programmer. In this research, we will show which language and platform are better for developers and programmers. We used 1139 Stack Overflow related commits, analyzed them and came to an end that in "JavaScript" language programmers involve most and in "Java", response time is less than other languages. We also found that in "Python", programmers have a large probability to get an answer. We also analyzed different platforms in Stack Overflow and fo...

Stack Overflow is the most popular Q&A website which is used by developers and programmers for many developments and programming purposes. Stack Overflow commits occur based on various types of programming languages. But among all the languages which are more reliable and helpful for programmers is a burning question. We researched over Stack Overflow commits and reached in a conclusion. Our main target was to analyze over Stack Overflow commits and to give a result which can raise the confidence level of a programmer. In this research, we will show which language and platform are better for developers and programmers. We used 1139 Stack Overflow related commits, analyzed them and came to an end that in "JavaScript" language programmers involve most and in "Java", response time is less than other languages. We also found that in "Python", programmers have a large probability to get an answer. We also analyzed different platforms in Stack Overflow and found that "Web Design" is the most helpful platform among all the platforms. From our research developers and programmers can now understand which platform and language they should choose.

We are concerned that the quality of results produced by an NLP parser bears little, if any, relation to the percentage-results claimed by the various NLP parser-systems presently available for use. To illustrate this problem we examine one readily available NLP tagging and parsing system, the ENGCG parser, and one tagger, the Brill tagger.