The Strengths and Limitations of the Statistical Modeling of Complex Social Phenomenon: Focusing on SEM, Path Analysis, or Multiple Regression Models
This paper analyzes the conceptual framework of three
statistical methods, multiple regression, path analysis, and structural
equation models. When establishing research model of the statistical
modeling of complex social phenomenon, it is important to know the
strengths and limitations of three statistical models. This study
explored the character, strength, and limitation of each modeling and
suggested some strategies for accurate explaining or predicting the
causal relationships among variables. Especially, on the studying of
depression or mental health, the common mistakes of research
modeling were discussed.
[1] MacCallum, R. C., & Austin, J. T. (2000). Applications of Structural
Equation Modeling in Psychological Research. Annual Review of
Psychology, 51(1), 201-226. doi: doi:10.1146/annurev.psych.51.1.201
[2] Pedhazur, E. J. (1997). Multiple regression in behavioral research (Third
ed.). Fort Worth, TX: Harcourt Brace College Publishers.
[3] Darlington, R.B. (1968). Multiple Regression In Psychological Research
And Practice. Psychological Bulletin, Vol 69(3), 161-182. [4] Ward, J. H. (1969).Synthesizing Regression Models -- An Aid to
Learning Effective Problem Analysis,'' The American Statistician, 23,
14-20.
[5] Goldberger A.S. (1991) A course in econometrics. Cambridge, MA.
Harvard University Press.
[6] Lewis-Beck M.S. and Skalaban A.(1991) The R-squared: Some straight
talk In J. A. Stimson (Ed.) Political analysis: Vol 2. Ann Arbor MI: The
University of Michigan.
[7] Cohen J. and Cohen P. (1983) Applied multiple regression/correlation
analysis for the behavioral sciences (2nd. Ed.). Hillsdale, NJ: Lawrence
Erlbaum Associates.
[8] Mallinckrodt, B. (1992) Childhood emotional bonds with parents,
development of adult social competencies, and availability of social
support. Journal of Counseling Psychology, 39, 453-461.
[9] Konovsky, M.A. Folger, R. &Cropanzano, R. (1987) Relative effects of
procedural and distributive justice on employee attitudes. Representative
Research in Social Psychology, 17, 15-24.
[10] Rutter M. (2007) Proceeding from observed correlation to causal
inference: the use of natural experiments, Perspectives on Psychological
Science, 2 (4): 377-395
[11] Mitchell, R. J. (1992). Testing Evolutionary and Ecological Hypotheses
Using Path Analysis and Structural Equation Modelling. Functional
Ecology, 6(2), 123-129.
[12] Petraitis, P. S., Dunham, A. E., &Niewiarowski, P. H. (1996). Inferring
multiple causalities: The Limitations of Path Analysis. Functional
Ecology, 10(4), 421-431.
[13] Myers R. (1990). Classical and modern regression with applications 2nd
ed. Duxbury Press, Boston
[14] Hoyle, R.H.&Panter, A.T. (1995) Writing about structural equation
models. In R.H. Hoyle (Ed.), Structural equation modeling: Comments,
issues and applications. 158-176. Thousand Oaks, CA:Sage
[15] Joreskog K.G. and Sorbom, D. (1993) LISREL8: Structural equation
modeling with the SIMPLIS command language. Hillsdale, NJ: Lawrence
Erlbaum Associates.
[1] MacCallum, R. C., & Austin, J. T. (2000). Applications of Structural
Equation Modeling in Psychological Research. Annual Review of
Psychology, 51(1), 201-226. doi: doi:10.1146/annurev.psych.51.1.201
[2] Pedhazur, E. J. (1997). Multiple regression in behavioral research (Third
ed.). Fort Worth, TX: Harcourt Brace College Publishers.
[3] Darlington, R.B. (1968). Multiple Regression In Psychological Research
And Practice. Psychological Bulletin, Vol 69(3), 161-182. [4] Ward, J. H. (1969).Synthesizing Regression Models -- An Aid to
Learning Effective Problem Analysis,'' The American Statistician, 23,
14-20.
[5] Goldberger A.S. (1991) A course in econometrics. Cambridge, MA.
Harvard University Press.
[6] Lewis-Beck M.S. and Skalaban A.(1991) The R-squared: Some straight
talk In J. A. Stimson (Ed.) Political analysis: Vol 2. Ann Arbor MI: The
University of Michigan.
[7] Cohen J. and Cohen P. (1983) Applied multiple regression/correlation
analysis for the behavioral sciences (2nd. Ed.). Hillsdale, NJ: Lawrence
Erlbaum Associates.
[8] Mallinckrodt, B. (1992) Childhood emotional bonds with parents,
development of adult social competencies, and availability of social
support. Journal of Counseling Psychology, 39, 453-461.
[9] Konovsky, M.A. Folger, R. &Cropanzano, R. (1987) Relative effects of
procedural and distributive justice on employee attitudes. Representative
Research in Social Psychology, 17, 15-24.
[10] Rutter M. (2007) Proceeding from observed correlation to causal
inference: the use of natural experiments, Perspectives on Psychological
Science, 2 (4): 377-395
[11] Mitchell, R. J. (1992). Testing Evolutionary and Ecological Hypotheses
Using Path Analysis and Structural Equation Modelling. Functional
Ecology, 6(2), 123-129.
[12] Petraitis, P. S., Dunham, A. E., &Niewiarowski, P. H. (1996). Inferring
multiple causalities: The Limitations of Path Analysis. Functional
Ecology, 10(4), 421-431.
[13] Myers R. (1990). Classical and modern regression with applications 2nd
ed. Duxbury Press, Boston
[14] Hoyle, R.H.&Panter, A.T. (1995) Writing about structural equation
models. In R.H. Hoyle (Ed.), Structural equation modeling: Comments,
issues and applications. 158-176. Thousand Oaks, CA:Sage
[15] Joreskog K.G. and Sorbom, D. (1993) LISREL8: Structural equation
modeling with the SIMPLIS command language. Hillsdale, NJ: Lawrence
Erlbaum Associates.
@article{"International Journal of Business, Human and Social Sciences:69951", author = "Jihye Jeon", title = "The Strengths and Limitations of the Statistical Modeling of Complex Social Phenomenon: Focusing on SEM, Path Analysis, or Multiple Regression Models", abstract = "This paper analyzes the conceptual framework of three
statistical methods, multiple regression, path analysis, and structural
equation models. When establishing research model of the statistical
modeling of complex social phenomenon, it is important to know the
strengths and limitations of three statistical models. This study
explored the character, strength, and limitation of each modeling and
suggested some strategies for accurate explaining or predicting the
causal relationships among variables. Especially, on the studying of
depression or mental health, the common mistakes of research
modeling were discussed.", keywords = "Multiple regression, path analysis, structural equation
models, statistical modeling, social and psychological phenomenon.", volume = "9", number = "5", pages = "1634-9", }