Skip to main content
SpringerLink
Log in

Alternative common factor models for multivariate biometric analyses

  • Published:
Behavior Genetics Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Behrman, J., Taubman, P., and Wales, T. (1977). Controlling for and measuring the effects of genetics and family environment in equations for schooling and labor market success. In Taubman, P. (ed.),Kinometrics: Determinants of Socioeconomic Success Within and Between Families, North-Holland, Amsterdam.

    Google Scholar 

  • Bock, R. D. (1989).Multilevel Analysis of Educational Data, Academic Press, San Diego.

    Google Scholar 

  • Bock, R. D., and Vandenberg, S. G. (1968). Components of heritable variation in mental test scores, In Vandenberg, S. G. (ed.),Progress in Human Behavior Genetics, Johns Hopkins Press, Baltimore.

    Google Scholar 

  • Boomsma, D. I., and Gabrielli, W. F. (1985). Behavioral genetic approaches to psychophysiology data.Psychophysiology 22:249–260.

    PubMed  Google Scholar 

  • Boomsma, D. I., and Molenaar, P. C. M. (1986). Using LISREL to analyze genetic and environmental covariance structure.Behav. Genet. 16: 237–250.

    Google Scholar 

  • Cantor, R. M., Nance, W. E., Eaves, L. J., Winter, P. M., and Blanchard, M. M. (1983). Analysis of the covariance structure of digital ridge counts in the offspring of monozygotic twins.Genetics 103:495–512.

    PubMed  Google Scholar 

  • Carey, G. (1986). A general multivariate approach to linear modeling in human genetics.Am. J. Hum. Genet. 39:775–786.

    PubMed  Google Scholar 

  • Cattell, R. B. (1960). The multiple abstract variance analysis equations and solutions: For nature-nuture research on continoous variables.Psychol. Rev. 67:353–372.

    PubMed  Google Scholar 

  • Cattell, R. B. (1982).The Inheritance of Personality and Ability: Research Methods and Findings, Academic Press, New York.

    Google Scholar 

  • Chamberlain, G., and Grilliches, Z. (1977). More on brothers. In Taubman, P. (ed.),Kinometrics: Determinants of Socioeconomic Success Within and Between Families, North-Holland, Amsterdam.

    Google Scholar 

  • Crawford, C. B., and DeFries, J. C. (1978). Factor analysis of genetic and environmental correlation matrices.Multivar. Behav. Res. 13:297–318.

    Google Scholar 

  • DeFries, J. C. (1979). Comment on Fulker's “Some implications of biometrical genetical analysis for psychological research,” In Royce, J. R., and Mos, L. P. (eds.),Theoretical Advances in Behavior Genetics, Sijthoff & Noordhoff, Alphen aan den Rijn, The Netherlands, pp. 381–383.

    Google Scholar 

  • Eaves, L. J., Martin, N. B., and Eysenck, S. B. G. (1977). An application of the analysis of covariance structures to the psychogenetical study of impulsiveness.Br. J. Math. Stat. Psychol. 30:1–42.

    Google Scholar 

  • Eaves, L. J., Last, K. A., Young, P. A., and Martin, N. G. (1978). Model-fitting approaches to the analysis of human behavior.Heredity 41:249–320.

    PubMed  Google Scholar 

  • Fraser, C. (1979).COSAN User's Guide, Ontarior Institute for Studies in Education, Toronto (Note: Center for Behavioral Studies, University of New England, Armidale, N.S.W., Australia).

    Google Scholar 

  • Fulker, D. W. (1978). Multivariate extensions of a biometrical model of twin data. In Nance, W. E., et al., (eds.),Twin Research: Psychology and Methodology, Liss, New York, pp. 217–236.

    Google Scholar 

  • Fulker, D. W. (1979). Some implications of biometrical genetical analysis for psychological research. In Royce, J. R., Mos, L. P. (eds.),Theoretical Advances in Behavior Genetics, Sitjhoff & Noordhoff, Alphen aan den Rijn, The Netherlands.

    Google Scholar 

  • Fulker, D. W., Baker, L. A., and Bock, R. D. (1983). Estimating components of covariance using LISREL.Data Anal. Commun. Comp. Data Anal. 14:261–281.

    Google Scholar 

  • Goldberger, A. S. (1978). Pitfalls in the resolution of intelligence inheritance. In Morton, N. E., and Chang, C. S. (eds.),Genetic Epidemiology, Academic Press,New York, pp. 30–45.

    Google Scholar 

  • Goldsmith, H. H. (1984). Continuity of personality: A genetic perspective.In Emde, R. M., and Harmon, R. J. (eds.),Continuities and Discontinuities in Development,Plenum, New York.

    Google Scholar 

  • Goldsmith, H. H. (1983). Genetic influences on personality from infancy to adulthood.Child Dev. 54:331–355.

    PubMed  Google Scholar 

  • Henderson, N. D. (1982). Human behavior genetics.Annu. Rev. Psychol. 33:403–440.

    PubMed  Google Scholar 

  • Horn, J. L. (1986). Intellectual ability concepts. In Sternberg, R. J. (ed.),Advances in the Psychology of Human Intelligence, Erlbaum, Hillsdale, N. J.

    Google Scholar 

  • Horn, J. L., and McArdle, J. J. (1980). Perspectives on mathematical and statistical model building (MASMOB) in aging research. In Poon, L. W. (ed.),Aging in the 1980s: Contemporary Perspectives, American Psychological Association, Washington, D.C.

    Google Scholar 

  • Jaspars, J. M. F., and deLeeuw, J. A. (1980). Genetic-environment covariation in human behaviour genetics. In van der Kamp, L. J. Th., Langerak, W. F., and de Gruijter, D. N. M. (eds.),Psychometrics for Educational Debates, Wiley, New York.

    Google Scholar 

  • Jinks, J. L., and Fulker, D. W. (1970). Comparison of the biometrical genetical, MAVA, and classical approaches to the analysis of human behavior.Psychol. Bull.73:311–349.

    PubMed  Google Scholar 

  • Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis.Psychometrika 34:183–202.

    Google Scholar 

  • Jöreskog, K. G. (1970). A general model for the analysis of covariance structures.Biometrika 57:239–251.

    Google Scholar 

  • Jöreskog, K. G., and Sörbom, D. (1979). In Magidson, J. (ed.),Advances in Factor Analysis and Structural Equation Models, Abt Books, Cambridge, Mass.

    Google Scholar 

  • Kempthorne, O., and Osborne, R. H. (1961). The interpretation of twin data.Am.J. Hum. Genet. 13:320–329.

    PubMed  Google Scholar 

  • Lange, K., and Boehnke, M. (1983). Extensions to pedigree analysis. IV. Covariance component models for multivariate traits.Am. J. Med. Genet. 14:513–524.

    PubMed  Google Scholar 

  • Loehlin, J. C. (1987).Latent Variable Models: An Introduction to Factor, Path, and Structural Analysis, Erlbaum, Hillsdale, N.J.

    Google Scholar 

  • Loehlin, J. C. (1978). Heredity-environment analyses of Jenck's IQ correlations.Behav. Genet. 8:(5):415–435.

    PubMed  Google Scholar 

  • Loehlin, J. C. (1979). Combining data from different groups in human behavior genetics. In Royce, J. R., and Mos, L. P. (eds.),Theoretical Advances in Behavior Genetics, Sijthoff & Noordhoff, Germantown, Md.

    Google Scholar 

  • Loehlin, J. C., and Vandenberg, S. G. (1968). Genetic and environmental components in the covariation of cognitive abilities: An additive model. In Vandenberg, S. G. (ed.),Progress in Human Behavior Genetics, Johns Hopkins Press, Baltimore.

    Google Scholar 

  • Martin, N. G., and Eaves, L. G. (1977). The genetical analysis of covariance structure.Heredity 138:(1):79–95.

    Google Scholar 

  • Martin, N. G., Eaves, L. J., and Fulker, D. W. (1979). The genetical relationship of impulsiveness and sensation seeking to Eysenck's personality dimensions.Acta Genet. Med. Gemellol. 28:197–210.

    PubMed  Google Scholar 

  • Martin, N. G., Jardine, R., and Eaves, L. J. (1984). Is there only one set of genes for different abilities.Behav. Genet. 14:355–370.

    Google Scholar 

  • Martin, N. G., Boomsma, D. I. and Neale, M. C. (1989). Forward.Behav. Genet. 19:5–7.

    Google Scholar 

  • McArdle, J. J. (1980). Causal modeling applied to psychonomic systems simulation.Behav. Res. Methods Instrument. 12:193–209.

    Google Scholar 

  • McArdle, J. J. (1986). Latent growth within behavior genetic models.Behav. Genet. 16:163–200.

    PubMed  Google Scholar 

  • McArdle, J. J. (1988). Dynamic but structural equation modeling of repeated measures data. In Nesselroade, J. R., and Cattell, R. B. (eds.),Handbook of Multivariate Experimental Psychology, Vol. II, Plenum Press, New York pp. 561–614.

    Google Scholar 

  • McArdle, J. J. and Boker, S. M. (1990),RAMpath: Computer software for path diagrams and path analysis. Denver, CO: Data Transforms.

    Google Scholar 

  • McArdle, J. J., and Goldsmith, H. H. (1984). Structural equation modeling applied to the twin design: Comparative multivariate models of the WAIS.Behav. Genet. 14:609 (abstract).

    Google Scholar 

  • McArdle, J. J., Goldsmith, H. H., and Horn, J. L. (1981). Genetic structural equation models of fluid and crystallized intelligence.Behav. Genet. 11:607 (abstract).

    Google Scholar 

  • McArdle, J. J., and Gottesman, I. I. (1987). Some models where independent ≠ different: A response to Plomin & Daniels.Behav. Brain Sci. 10(1):31–32.

    Google Scholar 

  • McArdle, J. J., and Horn, J. L. (1990). An effective graphic representation for linear structural equation models.Multivar. Behav. Res. (in press).

  • McArdle, J. J., and McDonald, R. P. (1984). Some algebraic properties of the Reticular Action Model for moment structures.Br. J. Math. Stat. Psychol. 37:234–251.

    PubMed  Google Scholar 

  • McArdle, J. J., Connell, J. P., and Goldsmith, H. H. (1980). Structural modeling of stability and genetic influence: Some results from a longitudinal study of behavioral style.Behav. Genet. 10:487.

    Google Scholar 

  • McDonald, R. P. (1985).Factor Analysis and Related Methods, N.J. Erlbaum, Hillsdale.

    Google Scholar 

  • McDonald, R. P., and Krane, W. R. (1979). A Monte Carlo study of local identifiability and degrees of freedom in the asymptotic likelihood ratio test.Br. J. Math. Stat. Psychol 32:121–132.

    Google Scholar 

  • Meredith, W. (1968). Factor analysis and the use of inbred strains. In Vandenberg, S. G. (ed.),Progress in Human Behavior Genetics, Johns Hopkins Press, Baltimore.

    Google Scholar 

  • Neale, M. C. and McArdle, J. J. (1990). The analysis of assortative mating: A LISREL model.Behavior Genetics,20(2):287–293.

    PubMed  Google Scholar 

  • Plomin, R., and Daniels, D. (1987) Why are children in the same family so different?Behav. Brain Sci. 10:37.

    Google Scholar 

  • Roudabush, G. (1968), Analyzing dyadic relationships. In Vandenberg, S. G. (ed.),Progress in Human Behavior Genetics, Johns Hopkins Press, Baltimore.

    Google Scholar 

  • Royce, J. R. (1979). The factor-gene basis of individuality. In Royce, J. R., and Mos, L. P. (eds.),Theoretical Advances in Behavior Genetics, Sijthoff & Noordhoff, Alphen aan den Rijn, The Netherlands.

    Google Scholar 

  • Spearman, D. (1904). General intelligence objectively determined and measured.Am. J. Psychol. 15:201–293.

    Google Scholar 

  • Tambs, K., Sundet, J. M., and Magnus, P. (1984). Heritability analysis of the WAIS subtests. A study of twins.Intelligence 8:283–293.

    Google Scholar 

  • Taubman, P. (1978). Determinants of socioeconomic success: Regression and latent variable analysis in samples of twins. In Nance, W. E., et al., (eds.),Twin Research: Psychology and Methodology, Liss, New York.

    Google Scholar 

  • Thurstone, L. L. (1947).Multiple Factor Analysis, University of Chicago Press, Chicago.

    Google Scholar 

  • Vandenberg, S. G. (ed.), (1968).Progress in Human Behavior Genetics: Recent Reports on Genetic Syndromes, Twin Studies, and Statistical Advances, Johns Hopkins Press, Baltimore.

    Google Scholar 

  • Wright, S. (1921). Correlation and causation.J. Agr. Res. 20:557–585.

    Google Scholar 

  • Wright, S. (1982). On “Path analysis in genetic epidemiology: A critique.”Am. J. Hum. Genet. 35:757–762.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Psychology, University of Virginia, 22903, Charlottesville, Virginia

    J. J. McArdle

  2. Department of Psychology, University of Oregon, 97403, Eugene, Oregon

    H. H. Goldsmith

Authors
  1. J. J. McArdle
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. H. H. Goldsmith
    View author publications

    You can also search for this author in PubMed Google Scholar

Additional information

This research has been supported by grants from the National Institute on Aging (AG02695, AG04704, and AG07137) to McArdle, and a Research Career Development Award (HD00694) to Goldsmith.

Rights and permissions

Reprints and permissions

About this article

Cite this article

McArdle, J.J., Goldsmith, H.H. Alternative common factor models for multivariate biometric analyses. Behav Genet 20, 569–608 (1990). https://doi.org/10.1007/BF01065873

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01065873

Key Words

Search

Navigation