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This article by Whelan (2010) is one of the best introductory papers I've found on the subject. Normalization is covered quite clearly and extensively, including the caveats and "gotchas". References Whelan, R. (2010). Effective analysis of reaction time data. The Psychological Record, 58(3), 9.


My impression is that, recently, a consensus began to form recently that RTs should be transformed to satisfy model assumptions. This is especially true when data is analyzed with mixed models instead of ANOVAs. Concerning the stability of effects under different transformations, you may find this paper interesting: http://web.uvic.ca/psyc/masson/KMR10.pdf


You can transform RT, i.e., by log(1/RT). This makes the distribution roughly normal. The problem is that you don't usually run the ANOVA on the RT values collected at each trial, but on the average for each participant. So the distribution across participants need to be normal. A trick is to transform the single RT values, calculate the mean for each ...


NEO FFI Scoring The test manual describes how to calculate raw scores for the NEO-FFI. If you have been asked to do an analysis of the NEO-FFI then you should be given access to relevant details in the test manual. If you don't have access, you may wish to contact your local psychology department. They will often have a test library with the NEO-FFI manual. ...

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