Cohen`s number was executed to determine whether there was agreement between the verdict of two police officers that 100 people were behaving normally or suspiciously in a shopping mall. There was a moderate convergence between the judgments of the two officers, n. 593 (95% CI, 300 to 886), p < .0005. You can see that Cohens is Kappa () .593. This is the part of the agreement beyond the agreement of chance. Cohens Kappa () can range from -1 to 1. On the basis of Altman`s (1999) guidelines, adapted by Landis-Koch (1977), a Kappa (No. 593) represents a moderate approval force. < Our Kappa coefficient is statistically significantly different from zero. In research projects in which you have two or more advisors (also known as "judge" or observer) responsible for measuring a variable on a category scale, it is important to determine whether such evaluators agree. Cohens Kappa () is such a measure for the Inter-Rater agreement for categorical scales when there are two advisers (the Greek letter is "kappa" in tiny). Agresti, A (2002). Category data analysis (2.
New York: Wiley. (p. 435). Fleiss, J.L., Cohen, J. (1973). The equivalence of the weighted kappa and the intraclass correlation coefficient is a measure of reliability. Educational and psychological measure, 33, 613-619. Perhaps you`d also like: Valiquette, C.A.M., Lesage, A.D., Mireille, C. (1994), Kappa computing cohen coefficients with SPSS MATRIX. “Behavior Research Methods, Instruments, Computers,” 26 (1), 60-61.
Valiquette et al. show the SPSS MATRIX code for weighted and unweighted Kappa examples from Cohen`s original documents. Weights are contained in Data LIST-END DATA DATA commands as a matrix adjacent to the number matrix instead of being calculated in computE commands. In this way, the user can specify weights for each conflict cell that are not necessarily a function of the distance between the line and the column of that cell. Wixon, D. R. (1979). Cohens Kappa-Coefficient of the Observation Agreement: A BASIC program for mini-computers. Behavior Research Methods – Instrumentation,11, 602.
Reliability assessment between rating agencies (ACCORD, also known as the Inter-Rater Agreement) is often necessary for research projects that collect data through evaluations of trained or untrained coders. However, many studies use false statistical analyses to calculate ERREURS, misinterpret the results of IRR analyses, or disrepresent the implications that IRR estimates have on statistical performance for subsequent analyses. Higher levels of CCI suggest better irregage, an ICC estimate of 1 indicating perfect matching, and random matching of 0. Negative CCI estimates indicate systematic discrepancies and some ICCs may be less than $1 for three or more codes.