Cochran's Q test

Cochran's test is a non-parametric statistical test to verify whether k treatments have identical effects in the analysis of two-way randomized block designs where the response variable is binary.[1][2][3] It is named after William Gemmell Cochran. Cochran's Q test should not be confused with Cochran's C test, which is a variance outlier test. Put in simple technical terms, Cochran's Q test requires that there only be a binary response (e.g. success/failure or 1/0) and that there be more than 2 groups of the same size. The test assesses whether the proportion of successes is the same between groups. Often it is used to assess if different observers of the same phenomenon have consistent results (interobserver variability).[4]

  1. ^ William G. Cochran (December 1950). "The Comparison of Percentages in Matched Samples". Biometrika. 37 (3/4): 256–266. doi:10.1093/biomet/37.3-4.256. JSTOR 2332378.
  2. ^ Conover, William Jay (1999). Practical Nonparametric Statistics (Third ed.). Wiley, New York, NY USA. pp. 388–395. ISBN 9780471160687.
  3. ^ National Institute of Standards and Technology. Cochran Test
  4. ^ Mohamed M. Shoukri (2004). Measures of interobserver agreement. Boca Raton: Chapman & Hall/CRC. ISBN 9780203502594. OCLC 61365784.