Taxometric and Factor Analytic Models of Anxiety Sensitivity: Integrating Approaches to Latent Structural Research

Autor/inn/en	Bernstein, Amit; Zvolensky, Michael J.; Norton, Peter J.; Schmidt, Norman B.; Taylor, Steven; Forsyth, John P.; Lewis, Sarah F.; Feldner, Matthew T.; Leen-Feldner, Ellen W.; Stewart, Sherry H.; Cox, Brian
Titel	Taxometric and Factor Analytic Models of Anxiety Sensitivity: Integrating Approaches to Latent Structural Research
Quelle	In: Psychological Assessment, 19 (2007) 1, S.74-87 (14 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1040-3590
Schlagwörter	North Americans; Anxiety; Factor Structure; Measures (Individuals); Adults; Models; Factor Analysis; Evaluation Methods + Suchen Sie Ihr Suchwort? Angst; Faktorenstruktur; Messdaten; Analogiemodell; Faktorenanalyse
Abstract	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. (Author).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10