The advent of new types of multivariate techniques, such as covariance structureanalysis, has the potential for reshaping research on counseling processes.Covariance structure analysis is more theory driven and confirmatory in naturethan regression analysis. Following a description of its strengths and weaknesses, adetailed example is provided showing how the use of covariance structure analysiscan improve research sophistication and theory development in counselingpsychology.
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References
1.
Abush, R. , & Burkhead, E. J. (1984). Job stress in midlife working women: Relationships among personality type, job characteristics, and job tension. Journal of Counseling Psychology, 31, 36-44.
2.
Bentler, P. M. , & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, 588-606.
3.
Cliff, N. (1983). Some cautions concerning the application of causal modeling methods. Multivariate Behavioral Research, 18, 115-126.
4.
Cook, T. D. (1985). Postpositivist critical multiplism. In R. L. Shotland & M. M. Mark (Eds.), Social science and social policy (pp. 21-62). Newbury Park, CA: Sage.
5.
Cook, T. D. , & Campbell, D. T. (1978). Quasi-experimentation: Design and analysis issues for field settings. Chicago: Rand McNally.
6.
Duncan, O. D. (1975). Introduction to structural equation models. New York: Academic Press.
7.
Dwyer, J. H. (1983). Statistical models for the social and behavioral sciences. Oxford: Oxford University Press.
8.
Fouad, N. A. , Cudeck, R., & Hansen, J. C. (1984). Convergent validity of the Spanish and English forms of the Strong-Campbell Interest Inventory for bilingual Hispanic high school students. Journal of Counseling Psychology, 31, 339-348.
9.
Heise, D. R. (1975). Causal analysis. New York: John Wiley.
10.
James, L. R. , Mulaik, S. A., & Brett, J. M. (1982). Causal analysis: Assumptions, models, and data. Newbury Park, CA: Sage.
11.
James, L. R. , & Singh, K. (1978). An introduction to the logic, assumptions, and basic analytic procedures for two-stage least squares. Psychological Bulletin, 85, 1104-1122.
12.
Jöreskog, K. G. , & Sörbom, D. (1984). LISREL VI: Analysis of linear structural relation- ships by maximum likelihood, instrumental variables, and least squares methods. Uppsala, Sweden: University of Uppsala, Department of Statistics.
13.
Kenny, D. A. (1979). Correlation and causality. New York: John Wiley.
14.
Kenny, D. A. , & Judd, C. M. (1984). Estimating the nonlinear and interactive effects of latent variables. Psychological Bulletin, 96, 201-210.
15.
MacCallum, R. (1986). Specification searches in covariance structure modeling. Psychological Bulletin, 100, 107-120.
16.
Maruyama, G. , & McGarvey, B. (1980). Evaluating causal models: An application of maximum likelihood analysis of structural equations. Psychological Bulletin, 87, 502-512.
17.
Murphy, G. (1932). An historical introduction to modern psychology(3rd ed.). New York: Harcourt & Brace.
18.
Pepinsky, H. B. , Hill-Frederick, K., & Epperson, D. L. (1978). The Journal of Counseling Psychology as a matter of policies. Journal of Counseling Psychology, 25, 483-498.
19.
Stelzl, I. (1986). Changing a causal hypothesis without changing the fit: Some rules for generating equivalent path models. Multivariate Behavioral Research, 21, 309-331.
20.
Underwood, B. J. (1975). Individual differences as a crucible in theory construction. American Psychologist, 30, 128-134.
