Abstract
A growing number of child cognition researchers are using an object-manipulation, sequential-touching paradigm to explore young children’s conceptual abilities. Within this paradigm, it is essential to distinguish children’s intracategory touching sequences from those expected by chance. The sequentialtouching approach is congruent with a permutation testing model of statistical inference and is best modeled by sampled permutations as derived from Monte Carlo procedures. In this article, we introduce a computer program for generating Monte Carlo sequential-touching simulations. TouchStat permits users to determine their own specifications to simulate sequential touching to category exemplars across a wide range of task parameters. We also present Monte Carlo chance probabilities for the standard two-category, four-exemplar task, with sequences up to 30 touches long. Finally, we consider broader applications of the TouchStat program.
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Thanks go to Jean Mandler and colleagues for their sequentialtouching Monte Carlo initiative and for graciously making available the results of their Monte Carlo simulations. Special thanks go to Malinda Thomas for running the 785 simulations reported in the Appendix, and to Sandra Waxman and Peg Smith for their encouragement and helpful comments during preparation of the manuscript. Finally, we are grateful for our discussions with Dave Weininger and Hoben Thomas on issues pertaining to probability sampling.
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Dixon, W.E., Woodard, T. & Merry, M.S. TouchStat: A Monte Carlo program for calculating sequential touching probabilities. Behavior Research Methods, Instruments, & Computers 30, 592–604 (1998). https://doi.org/10.3758/BF03209476
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DOI: https://doi.org/10.3758/BF03209476