Proportional reduction in loss
From Wikipedia, the free encyclopedia
This article is orphaned as few or no other articles link to it. Please help introduce links in articles on related topics. (November 2007) |
Proportional reduction in loss (PRL) is a measure for data reliability (statistics) may be derived or evaluated. It was proposed by Bruce Cooil and Roland T. Rust in their 1994 paper. This measure is applicable when a researcher wants to assess the consensus between judges who are asked to code a number of items into mutually exclusive qualitative categories.
[edit] References
1. Cooil, B., and Rust, R. T. (1994), "Reliability and Expected Loss: A Unifying Principle," Psychometrika, 59, 203-216. (available here )
2. Rust, R. T., and Cooil, B. (1994), "Reliability Measures for Qualitative Data: Theory and Implications," Journal of Marketing Research, 31(1), 1-14. (available here)
3. Cooil, B., and Rust, R. T. (1995), "General Estimators for the Reliability of Qualitative Data," Psychometrika, 60, 199-220. (available here)