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Introduction
Deciding between categorical and dimensional models of latent variables is a fundamental and enduring issue in psychiatry and psychology, which taxometric analyses were designed to resolve. Developed by Paul Meehl and his colleagues, these procedures allow researchers to determine whether observed variation is underpinned by a non-arbitrary latent class, or 'taxon', such as a discrete psychopathology or personality type. Discovering taxa and distinguishing them from latent dimensions has broad implications for how personality and psychopathology should be conceptualized, assessed and explained.
If a latent variable is taxonic, for example, it must be conceptualized as an entity with real category boundaries that exist independent of social convention or descriptive convenience. If it is not taxonic then no boundary exists unless a manifest distinction such as a diagnostic threshold is imposed on arbitrary or pragmatic grounds. The appropriate way to assess a taxonic variable involves assigning cases to categories at the taxon boundary, but assessing non-taxonic variables involves quantifying variation along the entirety of an underlying continuum. Taxa are likely to spring from mechanisms that Meehl (1977) referred to as 'specific etiologies', such as single discrete causal factors, whereas non-taxonic variables generally result from the additive effects of multiple small causal influences. Determining whether or not a latent variable is best thought of as taxonic is a crucial scientific question and not merely a matter of theoretical taste or statistical botanizing.
The taxometric method makes this determination in a distinctive way. Unlike some more familiar statistical approaches to latent variable analysis, it does not impose a particular kind of structure, as cluster analysis presumes a categorical structure or factor analysis a set of underlying dimensions, but instead tests between these alternatives. Unlike most comparable forms of data analysis, it does not follow a null hypothesis testing approach to inference or yield a single definitive statistic. Where most other analyses use a single statistical procedure, the taxometric method seeks consistency among the findings of multiple mathematically independent procedures. Other analyses provide chiefly numerical output, whereas the output of taxometric analyses is largely graphical, based on the interpretation of curves. Despite these unusual features, the taxometric method has proven to be popular and versatile (Ruscio et al. 2006).
Taxometric analyses were first...