Abstract
We introduce the statistical approach to STA in four parts. First, we discuss fitting a linear model. This is a conceptually simpler, or at least more familiar, case which helps to motivate what is to follow. Second, we discuss a procedure for fitting a monotonic model based on monotonic regression. Third, we apply this procedure to observed data involving sample means and variance, and fourth, we describe a hypothesis testing procedure based on bootstrap resampling.
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Notes
- 1.
There is nothing special about these constraints on the location and scale of u—other choices could equally be made.
- 2.
Prince et al. (2012) provide an extensive treatment of partial orders in their Bayesian hypothesis testing approach to STA.
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Dunn, J.C., Kalish, M.L. (2018). Statistical Methodology. In: State-Trace Analysis. Computational Approaches to Cognition and Perception. Springer, Cham. https://doi.org/10.1007/978-3-319-73129-2_4
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DOI: https://doi.org/10.1007/978-3-319-73129-2_4
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