2007
DOI: 10.3758/bf03193160
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Testing the race model inequality: An algorithm and computer programs

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Cited by 186 publications
(201 citation statements)
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“…All calculations followed the algorithm for testing the independent-race model inequality (Ulrich, Miller, & Schröter, 2007). First, the 100 RTs generated by each participant for all target trials were sorted in ascending order to estimate 19 percentiles (the 5th through the 95th, at fivepercentage-point intervals).…”
Section: General Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…All calculations followed the algorithm for testing the independent-race model inequality (Ulrich, Miller, & Schröter, 2007). First, the 100 RTs generated by each participant for all target trials were sorted in ascending order to estimate 19 percentiles (the 5th through the 95th, at fivepercentage-point intervals).…”
Section: General Methodsmentioning
confidence: 99%
“…To produce the sum of CDFs for I and E trials, RTs for these trials were pooled together, and 19 quantiles were estimated on the basis of only the fastest 100 of the 200 trials. All calculations were conducted using a MATLAB script for computing the independentrace model test (Ulrich et al, 2007).…”
Section: General Methodsmentioning
confidence: 99%
“…Analyses of RT were carried out to test the race model inequality (for an exact description of the procedure see Ulrich, Miller, & Schröter, 2007; for bias corrections, see Kiesel, Miller, & Ulrich, 2007). The race model inequality was not violated in any condition, so the redundancy gain observed in this experiment could be consistent with race models as well as with coactivation models.…”
Section: Resultsmentioning
confidence: 99%
“…95%) for each participant. Race model violations occur if the difference B -D is significantly positive, which is evaluated by computing a separate paired t-test at each percentile across participants, and type I errors are avoided by using Bonferroni corrections (Ulrich et al, 2007). The race model inequality is rejected, and coactivation must be accepted if there is a significant violation of the inequality at any percentile.…”
Section: Methodsmentioning
confidence: 99%
“…Data analysis An algorithm developed by Ulrich, Miller, and Schrötter (2007),which does not require any large number of observations and allows the results to be aggregated across participants, was used to perform the race model evaluation. The algorithm estimates empirical CDFs for each participant and every stimulus condition and calculates the race model boundary B by adding the corresponding single-feature CDFs (right side of inequality 1).…”
Section: Methodsmentioning
confidence: 99%