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Three tests and three corrections: comment on Koen and Yonelinas (2010)
Yoonhee Jang1, Laura Mickes, John T Wixted
1Department of Psychology, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0109, USA.
Summary
The slope of the z-transformed receiver-operating characteristic (zROC) in memory experiments is typically less than 1. New analysis shows previous tests on encoding variability were flawed, and data actually support the mixture-unequal-variance signal-detection model.
Area of Science:
- Cognitive Psychology
- Psychophysics
- Memory Research
Background:
- The slope of the z-transformed receiver-operating characteristic (zROC) in recognition memory is usually < 1.
- This is often interpreted as greater target distribution variance than lure distribution variance.
- The encoding variability hypothesis suggests differing memory strength increments during study cause this.
Purpose of the Study:
- To re-evaluate the Koen and Yonelinas (2010) study on encoding variability and zROC slope.
- To determine if experimental errors in Koen and Yonelinas's tests affected their conclusions.
- To assess the validity of the mixture-unequal-variance signal-detection (UVSD) model in light of these findings.
Main Methods:
- Analysis of the experimental design and statistical tests used by Koen and Yonelinas (2010).
- Correction of identified errors in the three statistical tests performed on mixed-strength target data.
- Comparison of corrected results against predictions of the encoding variability hypothesis and the mixture-UVSD model.
Main Results:
- The three tests performed by Koen and Yonelinas do not invalidate the encoding variability hypothesis.
- Errors were found in all three of Koen and Yonelinas's statistical tests.
- Corrected analyses show the data support the mixture-UVSD model, contradicting Koen and Yonelinas's original conclusion.
Conclusions:
- The encoding variability hypothesis remains a viable explanation for zROC slopes < 1.
- Koen and Yonelinas's (2010) conclusions were based on flawed statistical tests.
- The mixture-unequal-variance signal-detection model is supported by the re-analyzed data.
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