Behavior Genetics

, Volume 20, Issue 5, pp 569–608

Alternative common factor models for multivariate biometric analyses

  • J. J. McArdle
  • H. H. Goldsmith

DOI: 10.1007/BF01065873

Cite this article as:
McArdle, J.J. & Goldsmith, H.H. Behav Genet (1990) 20: 569. doi:10.1007/BF01065873


In prior research we have shown how linear structural equation models and computer programs (e.g., LISREL) may be simply and directly used to provide alternatives for the traditional biometric twin design. We use structural equations and path models to define biometric group differences, we write traditional common-factor models in the same way, and then we take a detailed look at some alternative multivariate and biometric models. We contrast the biometricfactors covariance structure approach used by Loehlin and Vandenberg (1968), Martin and Eaves (1977), and others with the psychometric-factors approach used by McArdle et al. (1980) and others. We use the multivariate primary mental abilities data on monozygotic (MZ) and dizygotic (DZ) twins from Loehlin and Vandenberg (1968) to detail fundamental differences in model specification and results. We extend both multivariate biometric approaches using exploratory and confirmatory multiple-factor models. These comparisons show that each alternative multivariate methodology has useful features for empirical applications.

Key Words

twins multivariate factor analysis structural equation models LISREL RAM intelligence primary mental abilities 

Copyright information

© Plenum Publishing Corporation 1990

Authors and Affiliations

  • J. J. McArdle
    • 1
  • H. H. Goldsmith
    • 2
  1. 1.Department of PsychologyUniversity of VirginiaCharlottesville
  2. 2.Department of PsychologyUniversity of OregonEugene

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