Taxometric and factor analytic models of anxiety sensitivity: Integrating approaches to latent structural research

Amit Bernstein, Michael J. Zvolensky, Peter J. Norton, Norman B. Schmidt, Steven Taylor, John P. Forsyth, Sarah F. Lewis, Matthew T. Feldner, Ellen W. Leen-Feldner, Sherry H. Stewart, Brian Cox

Research output: Contribution to journalArticleResearchpeer-review

70 Citations (Scopus)


This study represents an effort to better understand the latent structure of anxiety sensitivity (AS), as indexed by the 16-item Anxiety Sensitivity Index (ASI; S. Reiss, R. A. Peterson, M. Gursky, & R. J. McNally, 1986), by using taxometric and factor-analytic approaches in an integrative manner. Taxometric analyses indicated that AS has a taxonic latent class structure (i.e., a dichotomous latent class structure) in a large sample of North American adults (N = 2,515). As predicted, confirmatory factor analyses indicated that a multidimensional 3-factor model of AS provided a good fit for the AS complement class (normative or low-risk form) but not the AS taxon class (high-risk form). Exploratory factor analytic results suggested that the AS taxon may demonstrate a unique, unidimensional factor solution, though there are alternative indications that it may be characterized by a 2-factor solution. Findings suggest that the latent structural nature of AS can be conceptualized as a taxonic latent class structure composed of 2 types or forms of AS, each of these forms characterized by its own unique latent continuity and dimensional structure.

Original languageEnglish
Pages (from-to)74-87
Number of pages14
JournalPsychological Assessment
Issue number1
Publication statusPublished - 1 Mar 2007
Externally publishedYes


  • Anxiety disorders
  • Anxiety sensitivity
  • Factor analysis
  • Taxometrics

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