The path analysis controversy: A new statistical approach to strong appraisal of verisimilitude

Psychological Methods

Volumn 7, Issue 3, 2002, Pages 283-300

  Meehl, Paul E ^a   Waller, Niels G ^b  

^a UNIVERSITY OF MINNESOTA   (United States)

^b VANDERBILT UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; HUMAN; METHODOLOGY; PSYCHOLOGY; STATISTICAL MODEL;

HUMANS; MODELS, STATISTICAL; PSYCHOLOGY;

EID: 85047668616     PISSN: 1082989X     EISSN: None     Source Type: Journal    
DOI: 10.1037/1082-989X.7.3.283     Document Type: Article

References (56)

1. Aigner, D. J., Hsiao, C., Kapteyn, A., & Wansbeek, T. (1984). Latent variable models in econometrics. In Z. Griliches & M. D. Intriligator (Eds.), Handbook of econometrics (Vol. 2, pp. 1321-1393). Amsterdam: North-Holland.
2. Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103, 411-423.
3. Arbuckle, J. L. (1995). Amos for Windows. Analysis of moment structures (Version 3.5) [Computer software]. Chicago: SmallWaters.
4. Austin, J. T., & Wolfe, D. (1991). Theoretical and technical contributions to structural equation modeling: An updated annotated bibliography. Structural Equation Modeling, 3, 105-175.
5. Bentler, P. M. (1980). Multivariate analysis with latent variables: Causal modeling. Annual Review of Psychology, 31, 419-456.
6. Bentler, P. M. (1995). EQS Structural Equations Program manual. Encino, CA: Multivariate Software.
7. Berry, W. D. (1984). Nonrecursive causal models. Newbury Park, CA: Sage.
8. Bielby, W. T., & Hauser, R. M. (1977). Structural equation models. Annual Review of Sociology, 3, 137-161.
9. Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.
10. Breckler, S. J. (1990). Applications of covariance structure modeling in psychology: Cause for concern? Psychological Bulletin, 107, 260-273.
11. Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136-162). Newbury Park, CA: Sage.
12. Cliff, N. (1983). Some cautions concerning the application of causal modeling methods. Multivariate Behavioral Research, 18, 115-126.
13. Clogg, C. C., & Haritou, A. (1997). The regression method of causal inference and a dilemma confronting this method. In V. R. McKim & S. P. Turner (Eds.), Causality in crisis? Statistical methods and the search for causal knowledge in the social sciences (pp. 83-112). Notre Dame, IN: University of Notre Dame Press.
14. Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52, 281-302.
15. Cudeck, R. (1989). Analysis of correlation matrices using covariance structure models. Psychological Bulletin, 105, 317-327.
16. Cudeck, R., & Henley, S. J. (1991). Model selection in covariance structure analysis and the "problem" of sample size: A clarification. Psychological Bulletin, 109, 512-519.
17. Duncan, O. D. (1975). Introduction to structural equation models. New York: Academic Press.
18. Epstein, R. J. (1987). A history of econometrics. Amsterdam: Elsevier.
19. Foa, E. B., & Foa, U. G. (1980). Resource theory: Interpersonal behavior as exchange. In K. J. Gergen, M. S. Greenberg, & R. H. Willis (Eds.), Social exchange and advances in theory and research (pp. 77-94). New York: Plenum.
20. Freedman, D. A. (1987). As others see us: A case study in path analysis. Journal of Educational Statistics, 12, 101-128.
21. Freedman, D. A. (1997). From association to causation via regression. In V. R. McKim & S. P. Turner (Eds.), Causality in crisis? Statistical methods and the search for causal knowledge in the social sciences (pp. 113-161, 177-182). Notre Dame, IN: University of Notre Dame Press.
22. Holland, P. (1986). Causal inference, path analysis, and recursive structural equations models. In C. Clogg (Ed.), Sociological methodology (pp. 449-484). Washington, DC: American Sociological Association.
23. Hu, L., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model-misspecification. Psychological Methods, 3, 424-453.
24. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1-55.
25. James, L. R., Mulaik, S. A., & Brett, J. M. (1982). Causal analysis: Assumptions, models and data. Studying organizations: Innovations in methodology (Vol. 1). Beverly Hills, CA: Sage.
26. Jöreskog, K. G., & Sörbom, D. (2000). LISREL 8.30 user's reference guide [Computer software manual]. Chicago: Scientific Software.
27. Karlin, S., Cameron, E. C., & Chakraborty, R. (1983). Path analysis in genetic epidemiology: A critique. Journal of Human Genetics, 35, 695-732.
28. Kenny, D. A., & Judd, C. M. (1984). Estimating the non-linear and interactive effects of latent variables. Psychological Bulletin, 96, 201-210.
29. Lakatos, I. (1970). Falsification and the methodology of scientific research programmes. In I. Lakatos & A. Musgrave (Eds.), Criticism and the growth of knowledge (pp. 91-196). New York: Cambridge University Press.
30. Lee, S., & Hershberger, S. (1990). A simple rule for generating equivalent models in covariance structure modeling. Multivariate Behavioral Research, 25, 313-334.
31. Li, F., Harmer, P., Duncan, T. E., Duncan, S. C., Acock, A., & Boles, S. (1998). Approaches to testing interaction effects using structural equation modeling methodology. Multivariate Behavioral Research, 33, 1-39.
32. Linhart, H., & Zucchini, W. (1986). Model selection. New York: Wiley.
33. MacCallum, R. C., & Austin, J. T. (2000). Applications of structural equation modeling in psychological research. Annual Review of Psychology, 51, 201-226.
34. MacCallum, R. C., Wegener, D. T., Uchino, B. N., & Fabrigar, L. R. (1993). The problem of equivalent models in applications of covariance structure analysis. Psychological Bulletin, 114, 185-199.
35. Mayo, D. G. (1991). Novel evidence and severe tests. Philosophy of Science, 58, 574-585.
36. Mayo, D. G. (1996). Error and the growth of experimental knowledge. Chicago: University of Chicago Press.
37. McKim, V. R., & Turner, S. P. (1997). Causality in crisis? Statistical methods and the search for causal knowledge in the social sciences. Notre Dame, IN: University of Notre Dame Press.
38. Meehl, P. E. (1990). Appraising and amending theories: The strategy of Lakatosian defense and two principles that warrant using it. Psychological Inquiry, 1, 108-141, 173-180.
39. Meehl, P. E. (1997). The problem is epistemology, not statistics: Replace significance tests by confidence intervals and quantify accuracy of risky numerical predictions. In L. L. Harlow, S. A. Mulaik, & J. H. Steiger (Eds.), What if there were no significance tests? (pp. 393-425). Mahwah, NJ: Erlbaum.
40. Niles, H. E. (1922). Correlation, causation and Wright's theory of "path coefficients." Genetics, 7, 258-273.
41. Niles, H. E. (1923). The method of path coefficients -An answer to Wright. Genetics, 8, 256-260.
42. Olsson, U. H., Troye, S. V., & Howell, R. D. (1999). Theoretic fit and empirical fit: The performance of maximum likelihood versus generalized least squares estimation in structural equation models. Multivariate Behavioral Research, 34, 31-58.
43. Pearl, J. (2000). Causality: Models, reasoning, and inference. Cambridge, MA: Cambridge University Press.
44. Pedhazur, E. J. (1997). Multiple regression in behavioral research: Explanation and prediction (3rd ed). New York: Harcourt Brace.
45. Popper, K. (1962). Conjectures and refutations. New York: Basic Books.
46. Popper, K. (1977). The logic of scientific discovery. New York: Basic Books. (Original work published 1959)
47. Rettig, K. D., Leichtentritt, R. D., & Stanton, L. M. (1999). Understanding noncustodial fathers' family and life satisfaction from resource theory perspective. Journal of Family Issues, 20, 507-538.
48. Rodgers, R. C., & Maranto, C. L. (1989). Causal models of publishing productivity in psychology. Journal of Applied Psychology, 74, 636-649.
49. Rogosa, D. (1987). Causal models do not support scientific conclusions: A comment in support of Freedman. Journal of Educational Statistics, 12, 185-195.
50. Salmon, W. C. (1984). Scientific explanation and the causal structure of the world. Princeton, NJ: Princeton University Press.
51. Shipley, B. (2000). Cause and correlation in biology: A user's guide to path analysis, structural equations and causal inference. Cambridge, MA: Cambridge University Press.
52. Spirtes, P., Glymour, C., & Scheines, R. (2000). Causation, prediction, and search. Cambridge, MA: MIT Press.
53. Wolfram, S. (1999). The Mathematica book (4th ed.) [Computer software]. Champaign, IL: Wolfram Media; and New York: Cambridge University Press.
54. Wren, P. C. (1925). Beau Geste. New York: Stokes.
55. Wright, S. (1921). Correlation and causation. Journal of Agricultural Research, 20, 557-585.
56. Wright, S. (1923). The theory of path coefficients - A reply to Niles's criticism. Genetics, 8, 239-255.