The taxonicity of schizotypy: does the same taxonic class structure emerge from analyses of different attributes of schizotypy and from fundamentally different statistical methods?

Abstract

Findings on the population distribution of schizotypy consistently point toward an underlying class structure. However, past research is methodologically homogeneous, chiefly involving analysis of attribute-specific indicators and coherent cut kinetic methods such as maximum covariance (MAXCOV) analysis. Two questions are examined. Are different or overlapping classes identified from different attributes of the schizophrenia phenotype? Do fundamentally different approaches to analysis yield consistent results? Participants (n=1074) completed the Schizotypal Personality Questionnaire (SPQ). Following item screening, MAXCOV analyses were conducted iteratively on attribute-specific item sets (cognitive-perceptual, interpersonal, and disorganized) and a general item set. Latent variable modeling (factor analysis, latent class analysis, and factor-mixture modeling) was used to examine the consistency of the MAXCOV results using items retained in the general set following MAXCOV analysis. Attribute-specific and general item sets gave taxonic MAXCOV curves and base rates of 8.4-10.4% and 3.6%, respectively. Classes were not independent. No latent variable model emerged as uniquely superior but five models distinguished a small high-scoring class populated by members of the MAXCOV general class. Different attributes distinguished overlapping yet nonredundant taxa, and a general schizotypy taxon identified with MAXCOV was also identified in latent variable modeling.

Keywords: Factor-mixture modeling; General population distribution; Latent structure; MAXCOV; Psychosis; Schizophrenia; Taxometric analysis.