Departmental Papers (ASC)

Document Type

Journal Article

Date of this Version

7-2004

Publication Source

Human Communication Research

Volume

30

Issue

3

Start Page

411

Last Page

433

DOI

10.1111/j.1468-2958.2004.tb00738.x

Abstract

In a recent article published in this journal, Lombard, Snyder-Duch, and Bracken (2002) surveyed 200 content analyses for their reporting of reliability tests; compared the virtues and drawbacks of five popular reliability measures; and proposed guidelines and standards for their use. Their discussion revealed that numerous misconceptions circulate in the content analysis literature regarding how these measures behave and can aid or deceive content analysts in their effort to ensure the reliability of their data. This paper proposes three conditions for statistical measures to serve as indices of the reliability of data and examines the mathematical structure and the behavior of the five coefficients discussed by the authors, plus two others. It compares common beliefs about these coefficients with what they actually do and concludes with alternative recommendations for testing reliability in content analysis and similar data-making efforts.

Copyright/Permission Statement

This is the accepted version of the article which has been published in final form at http://dx.doi.org/10.1111/j.1468-2958.2004.tb00738.x

 

Date Posted: 22 March 2011

This document has been peer reviewed.