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TouchStat v. 3.00: A new and improved Monte Carlo adjunct for the sequential touching task

  • Published: August 2007
  • Volume 39, pages 407–414, (2007)
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TouchStat v. 3.00: A new and improved Monte Carlo adjunct for the sequential touching task
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  • Wallace E. Dixon1,
  • Robert M. Price1,
  • Michael Watkins2 &
  • …
  • Christine Brink3 
  • 680 Accesses

  • 2 Citations

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Abstract

The sequential-touching procedure is employed by researchers studying nonlinguistic categorization in toddlers. TouchStat 3.00 is introduced in this article as an adjunct to the sequential-touching procedure, allowing researchers to compare children’s actual touching behavior to what might be expected by chance. Advantages over the Thomas and Dahlin (2000) framework include ease of use, and fewer assumptive limitations. Improvements over TouchStat 1.00 include calculation of chance probabilities for multiple “special cases” and for immediate intercategory alternations. A new feature for calculating mean run length is also included.

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Author information

Authors and Affiliations

  1. Department of Psychology, East Tennessee State University, P.O. Box 70649, 37614, Johnson City, TN

    Wallace E. Dixon & Robert M. Price

  2. Mt. Gilead, Ohio

    Michael Watkins

  3. Medical University of Ohio, Toledo, Ohio

    Christine Brink

Authors
  1. Wallace E. Dixon
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  2. Robert M. Price
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  3. Michael Watkins
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  4. Christine Brink
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Corresponding author

Correspondence to Wallace E. Dixon.

Additional information

Portions of this article were previously presented at the Biennial Meetings of the International Conference on Infant Studies in May, 2004, in Chicago.

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Dixon, W.E., Price, R.M., Watkins, M. et al. TouchStat v. 3.00: A new and improved Monte Carlo adjunct for the sequential touching task. Behavior Research Methods 39, 407–414 (2007). https://doi.org/10.3758/BF03193010

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  • Received: 31 January 2006

  • Accepted: 01 April 2006

  • Issue date: August 2007

  • DOI: https://doi.org/10.3758/BF03193010

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Keywords

  • Negative Binomial Distribution
  • Individual Child
  • Monte Carlo Sampling
  • Target Child
  • Monte Carlo Program

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  1. Wallace E. Dixon View author profile

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