Causal modeling and the origins of path analysis

Theory and Science

Volumn 7, Issue 1, 2006, Pages

  Denis, Daniel J ^a   Legerski, Joanna ^a  

^a UNIVERSITY OF MONTANA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 33744821348     PISSN: 15275558     EISSN: 15275558     Source Type: Journal    
DOI: None     Document Type: Review

References (53)

1. Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103, 411-423.
2. Asher, H. B. (1976). Causal modeling. Sage University Paper series on Quantitative Applications in the Social Sciences, 07-003. Beverly Hills and London: Sage Publications.
3. Bentler, P. M. (1986). Structural modeling and Psychometrika: An historical perspective on growth and achievements. Psychometrika, 51, 35-51.
4. Blalock, H. M. (1961). Correlation and causality: The multivariate case. Social Forces, 39, 246-251.
5. Blalock, H. M. (1964). Causal inferences in nonexperimental research. Chapel Hill: University of North Carolina Press.
6. Blalock, H. M. (1991). Are there really any constructive alternatives to causal modeling? Sociological Methodology, 21, 325-335.
7. Bollen, K. (1989). Structural equations with latent variables. New York: Wiley.
8. Breckler, S. J. (1990). Applications of covariance structure modeling in psychology: Cause for concern? Psychological Bulletin, 107, 260-273.
9. Burks, B. S. (1928). The relative influence of nature and nurture upon mental development: A comparative study of foster parent-foster child resemblance and true parent-true child resemblance. The Twenty-Seventh Yearbook of the National Society for the Study of Education, 27, 219-316.
10. Castle, W. E. (1914). The nature of size factors as indicated by a study of correlation. Carnegie Institute of Washington Publications, 196, 51-55.
11. Davenport, C. B. (1917). Inheritance of stature. Genetics, 2, 313-389.
12. Desrosières, A. (1998). The politics of large numbers: A history of statistical reasoning. London: Harvard University Press.
13. Duncan, O. D., & Hodge, R. W. (1963). Education and occupational mobility: A regression analysis. The American Journal of Sociology, 68, 629-644.
14. Fisher Box, J. (1978). R. A. Fisher. The life of a scientist. New York: John Wiley & Sons.
15. Fox, J. (1997). Applied regression analysis, linear models, and related methods. London: Sage Publications.
16. Games, P. A. (1990). Correlation and causation: A logical snafu. Journal of Experimental Education, 58, 239-246.
17. Goldberger, A. S., & Duncan, O. D. (1973). Structural equation models in the social sciences. New York: Seminar Press.
18. Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis. New Jersey: Prentice Hall.
19. Heise, D. R. (1969). Problems in path analysis and causal inference. Sociological Methodology, 1, 38-73.
20. Irzik, G., & Meyer, E. (1987). Causal modeling: New directions for statistical explanation. Philosophy of Science, 54, 495-514.
21. Johnson, R. A., & Wichem, D. W. (2002). Applied multivariate statistical analysis. New Jersey: Prentice Hall.
22. Jöreskog, K. G. (1973). A general method for estimating a linear structural equation system. In A. S. Goldberger & O. D. Duncan, (Eds.), Structural Equation Models in the social sciences (pp. 85-112). New York: Academic Press.
23. Keesling, J. W. (1972). Maximum likelihood approaches to causal analysis. Ph.D. dissertation. Department of Education. New York: Wiley.
24. Kelloway, E. K. (1998). Using LISREL for structural equation modeling: A researcher's guide. London: Sage Publications.
25. Kenny, D. A. (1979). Correlation and causality. New York: Wiley.
26. Land, K. C. (1969). Principles of path analysis. Sociological Methodology, 1, 3-37.
27. Leeuw, J. D., Keller, W. J., & Wansbeek, T. (1983). Interfaces between econometrics and psychometrics. Annals of Applied Econometrics, 22, 1-12.
28. Lewontin, R. C. (1980). Theoretical population genetics in the evolutionary synthesis. In E. Mayr, & W. B. Provine, (Eds.), The evolutionary synthesis: Perspectives on the unification of biology (pp. 58-68). Cambridge: Harvard University Press.
29. MacCallum, R. C., & Austin, J. T. (2000). Applications of structural equation modeling in psychological research. Annual Review of Psychology, 51, 201-226.
30. Meehl, P. E., & Waller, N. G. (2002). The path analysis controversy: A new statistical approach to strong appraisal of verisimilitude. Psychological Methods, 7, 283-300.
31. Mulaik, S. A., & James, L. R. (1995). Objectivity and reasoning in science and structural equation modeling. In R. H. Hoyle, (Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 118-137). London: Sage Publications.
32. Niles, H. E. (1922). Correlation, causation and Wright's theory of "path coefficients." Genetics, 7, 258-273.
33. Niles, H. E. (1923). The method of path coefficients: An answer to Wright. Genetics, 8, 256-260.
34. Pearson, K. (1901). On lines and planes of closest fit to a system of points in space. Philosophical Magazine, 2, 559-572.
35. Pedhazur, E. J. (1982). Multiple regression in behavioral research: Explanation and prediction. New York: Holt, Rinehart and Winston, Inc.
36. Pedhazur, E. J. (1997). Multiple regression in behavioral research. New York: Wadsworth.
37. Porter, T. M. (1986). The rise of statistical thinking: 1820-1900. New Jersey: Princeton University Press.
38. Provine, W. B. (2001). The origins of theoretical population genetics. Chicago: University of Chicago Press.
39. Sava, F. A. (2002). Causes and effects of teacher conflict inducing attitudes towards pupils: A path analysis model. Teaching and Teacher Education, 18, 1007-1021.
40. Schumacker, R. E., & Lomax, R. G. (2004). A beginner's guide to structural equation modeling. New Jersey: Lawrence Erlbaum Associates.
41. Simon, H. A. (1957). Models of man. New York. Wiley.
42. Spearman, C. (1904). General intelligence, objectively determined and measured. American Journal of Psychology, 15, 201-293.
43. Tabachnick, B. G., & Fidell, L. S. (2001). Using multivariate statistics. Boston: Allyn and Bacon.
44. Werts, C. E., & Linn, R. L. (1970). Path analysis: Psychological examples. Psychological Bulletin, 74, 193-212.
45. Wiley, D. E. (1973). The identification problem for structural equation models with unmeasured variables. In A. S. Goldberger and O.D. Duncan, (Eds.), Structural equation models in the social sciences (pp. 69-83). New York: Seminar Press.
46. Wolfle, L. M. (1999). Sewall Wright on the method of path coefficients: An annotated bibliography. Structural Equation Modeling, 6, 280-291.
47. Wolfle, L. M. (2003). The introduction of path analysis to the social sciences, and some emergent themes: An annotated bibliography. Structural Equation Modeling, 10, 1-34.
48. Wright, S. (1918). On the nature of size factors. Genetics, 3, 367-374.
49. Wright, S. (1920). The relative importance of heredity and environment in determining the piebald pattern of guinea-pigs. Proceedings of the National Academy of Sciences, 6, 320-332.
50. Wright, S. (1921). Correlation and causation. Journal of Agricultural Research, 20, 557-585.
51. Wright, S. (1923). The theory of path coefficients: A reply to Niles's criticism. Genetics, 8, 239-255.
52. Wright, S. (1931). Statistical methods in biology. Journal of the American Statistical Association, 26, 155-163.
53. Yule, G. U., & Kendall, M. G. (1932). An introduction to the theory of statistics. New York: Hafner Publishing Company.