Differentiating Categories and Dimensions: Evaluating the Robustness of Taxometric Analyses

@article{Ruscio2009DifferentiatingCA,
  title={Differentiating Categories and Dimensions: Evaluating the Robustness of Taxometric Analyses},
  author={J. Ruscio and Walter Kaczetow},
  journal={Multivariate Behavioral Research},
  year={2009},
  volume={44},
  pages={259 - 280}
}
Interest in modeling the structure of latent variables is gaining momentum, and many simulation studies suggest that taxometric analysis can validly assess the relative fit of categorical and dimensional models. The generation and parallel analysis of categorical and dimensional comparison data sets reduces the subjectivity required to interpret results by providing an objective Comparison Curve Fit Index (CCFI). This study takes advantage of developments in the generation of comparison data to… Expand
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Can sample-specific simulations help detect low base-rate taxonicity?
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