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Sztemberg-Lewandowska Mirosława
Zagadnienie dobroci dopasowania w konfirmacyjnej analizie czynnikowej
Goodness-Of-Fit Measure in Confirmatory Factor Analysis
Prace Naukowe Akademii Ekonomicznej we Wrocławiu. Taksonomia (8), 2001, nr 906, s. 149-156, bibliogr. 18 poz.
Issue title
Klasyfikacja i analiza danych : teoria i zastosowania
Analiza czynnikowa
Factor analysis
Omówiono narzędzia będące podstawowymi miarami dobroci dopasowania modelu hipotecznego do danych. Należą do nich statystyka chi-kwadrat; indeks dobroci dopasowania Joreskoga i Sorboma; porównawcze indeksy dopasowania Bentlera i Bonetta oraz oszczędne indeksy dopasowania Jamesa i Mulaika.

Exploratory factor analysis (EFA) is used to detect the optimal group of main factors, which explain the correlation between observed variables. Factor model received by the use of EFA is often verified while using Confirmatory Factor Analysis (CFA). CFA lets us to measure the goodness-of-fit of a hypothetical model to the convariance structure of observed variables. Most common measures applied in literature are:
  1. the Chi-square Statistic;
  2. the Goodness-of-Fit Index (GFI) and Adjusted Goodness-of-Fit Index (AGFI) (Joreskog i Sorbom,1981);
  3. the Normed and Nonnormed Fit Index (NFI and NNFI, respectively) (Bentler i Bonett, 1980) as well as normed Comparative Fit Index (CFI) and nonnormed Fit Index (FI) (Bender, 1990);
  4. the Parsimony Goodness-of-Fit Index (PGFI) and Parismony Normed Fit Index (PNFI) (James, 1982; Mulaik, 1989).
  5. Each such measure has advantages and disadvantages that the researcher should be aware of before rejecting a particular structure or claiming to have constructed a well-fitting model based on any of the available fit indices. (original abstract)
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  1. Bentler P.M. (1990): Comparative fit Indexes in Structural Models. "Psychological Bulletin" 107(2), 238-246.
  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. Bollen K.A., Long J.S. (1993): Testing Structural Equation Models. Newbury Park, CA: Sage.
  4. Gatnar E. (1998): Analiza czynnikowa teoria i zastosowanie. Katowice.
  5. Hair J.F., Anderson R.E., Tatham R.L., Black W.C. (1995): Multivariate Data Analysis with Readings. Englewood Cliffs: Prentice-Hall.
  6. James L.R., Mulaik S.A., Brett J. (1982): Causal Analysis: Models, Assumptions and Data. Beverly Hills, CA: Sage.
  7. Joreskog K.G., Sorbom D. (1981): Analysis of Linear Structural Relationships by Maximum Likelihood and Least Squares Methods. "Research Report" 81-8, University of Uppsala, Sweden.
  8. Kim J.O., Mueller C.W. (1978): Factor Analysis. Statistical Methods and Practical Issues. Beverly Hills, Sage.
  9. Kline P. (1994): An Easy Guide to Factor Analysis. Routledge, London.
  10. Lewis-Beck M.S. (ed.) (1994): Factor Analysis and Related Techniques. Sage Publications, London.
  11. Mueller R.O. (1996): Basic Principles of Structural Equation Modeling, An Introduction to IJSREL and EQS. Springer, New York.
  12. Mulaik S.A., James L.R., Van Alstine J., Bennett N., Lind S., Stilwell C.D. (1989): Evaluation of Goodness-of-Fit Indices for Structural Equation Models. "Psychological Bulletin" 105(3), 430-445.
  13. Okóń J. (1960): Analiza czynnikowa w psychologii. Warszawa, PWN.
  14. Sztemberg M. (2000): Konfirmacyjna analiza czynnikowa jako weryfikacja eksploracyjnej analizy czynnikowej. W: Walesiak M. (red.): Pomiar w badaniach rynkowych i marketingowych. Prace Naukowe Akademii Ekonomicznej we Wrocławiu.
  15. Tanaka J.S. (1993): Multifaceted Conceptions of Fit in Structural Equation Models. In K.A. Bollen i J.S. Long (Eds.): Testing Structural Equation Models. Newbury Park, CA: Sage, 10-39.
  16. Tucker L.R. Lewis C. (1973): A Reliability Coefficient for Maximum Likelihood Factor Analysis: "Psychometrika" 38,1-10.
  17. Walesiak M. (1996): Metody analizy danych marketingowych. Warszawa, PWN.
  18. Zakrzewska M. (1994): Analiza czynnikowa w budowaniu i sprawdzaniu modeli psychologicznych. Poznań, UAM.
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