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Examining mixed unknown distributions (mud)
journal contribution
posted on 2023-06-08, 10:49 authored by Daniel B Wright, Elin M SkagerbergA function, written in R, for testing whether the distribution of responses in one condition can be considered a combination of the distributions from two other conditions is described. The important aspect of this function is that it does not make any assumptions about the shape of the distributions. It is based on the Kolmogorov—Smirnov D statistic. The function also allows the user to test more specific and, hence, more statistically powerful hypotheses. One hypothesis, that the mixture does not capture the middle third of the distribution, is included as a built-in option, and code is provided so that other alternatives can easily be run. A power analysis reveals that the function is most likely to detect a difference between the combined conditions’ distribution and the other distribution when the center of the other distribution is near the midpoint of the two original distributions. Critical p values are estimated for each set of distributions, using bootstrap methods. An example from human memory research, exploring the blending hypothesis of the misinformation effect, is used for illustrative purposes.
History
Publication status
- Published
Journal
Behavior Research MethodsISSN
1554-351XPublisher
Springer VerlagExternal DOI
Issue
1Volume
40Page range
73-83Department affiliated with
- Psychology Publications
Full text available
- No
Peer reviewed?
- Yes
Legacy Posted Date
2012-08-28Usage metrics
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