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State-Trace Analysis

Part of the book series: Computational Approaches to Cognition and Perception ((CACP))

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Abstract

We illustrate the application of the STACMR software package to data derived from some additional experimental designs. These include both fully repeated and fully randomized factors, with examples of both significant and nonsignificant deviations from monotonicity. We discuss the problem of near-degeneracy, where one or both dependent variables are unaffected by the experimental factors.

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Notes

  1. 1.

    For clarity, associated error bars have been suppressed.

  2. 2.

    The astute reader will have noted that this corresponds to a single dissociation, demonstrating its lack of informativeness.

References

  • Dunn, J. C., Newell, B. R., & Kalish, M. L. (2012). The effect of feedback delay and feedback type on perceptual category learning: The limits of multiple systems. Journal of Experimental Psychology: Learning, Memory and Cognition, 38(4), 840–859.

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Authors and Affiliations

  1. School of Psychological Science, University of Western Australia, Perth, WA, Australia

    John C. Dunn

  2. Department of Psychology, Syracuse University, Syracuse, NY, USA

    Michael L. Kalish

Authors
  1. John C. Dunn
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  2. Michael L. Kalish
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Dunn, J.C., Kalish, M.L. (2018). More Examples. In: State-Trace Analysis. Computational Approaches to Cognition and Perception. Springer, Cham. https://doi.org/10.1007/978-3-319-73129-2_7

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