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MODEL BELİRLEMESİ, ÖRNEKLEM HACMİ VE TAHMİN YÖNTEMİNİN YAPISAL EŞİTLİK MODELLERİ UYUM ÖLÇÜTLERİNE ETKİSİ

Year 2013, Issue: 38, - , 01.06.2013

Abstract

Structural Equation Modeling (SEM) is a relatively new method, having its roots in the 1970s. Most applications have been in psychology, sociology, the biological sciences, educational research, political science, and market research. SEM is a modeling technique that can handle a large number of endogenous and exogenous variables, as well as latent variables specified as linear combinations of the observed variables. Because of this reason, the assessment of model fit in structural equation modeling (SEM) has long been a difficult issue in SEM applications. The use of Monte Carlo (MC) simulations for empirical assessment of statistical estimators and model fit is becoming more common in structural equation modeling. In this study, a Monte Carlo simulation study was conducted to investigate the effects on structural equation modeling (SEM) fit indices of, model specification, sample size and estimation method

References

  • BEARDEN, W.O., SHARMA, S. and TEEL, J. E. (1982). “Sample Size Effects on Chi Square and Other Statistics
  • Used in Evaluating Causal Models”, Journal of Marketing Research, 19: 425-430. BENTLER, P.M. and BONETT, D.G. (1980). “Significance Tests and Goodness of Fit in the Analysis of Covariance
  • Structures”, Psychological Bulletin, 88, 3: 588-606. BENTLER, P. M. (1990). “Comperative Fit Index in Structural Models”, Psychogical Bulletin, 10, 2: 238-246.
  • BOLLEN, K. A. (1989). Structural Equations with Latent Variables. New York: Wiley.
  • ENDERS, C. and FİNLEY, S. (2003). “SEM Fit Index Criteria Re-Examined: An Investigation of ML And Robust
  • Fit Indices in Complex Models”, Paper presented at the annual meeting of the American Educational Research Association, Chicago. FAN, X. and WANG, L. (1998). “Effects of Potantial Confounding Factors on Fit Indices and Parameter Estimates for True and Misspesified SEM Models”, Educational and Psychological Measurement, 58: 699-733.
  • FAN, X., THOMPSON, B. and WANG, L. (1999). “Effects of Sample Size, Estimation Methods, and Model
  • Specification on Structural Equation Modeling Fit Indexes”, Structural Equation Modeling: A Multidisciplinary Journal, 6, 1: 56-83. FAN, X. and SİVO, S.A. (2005). “Sensitivity of Fit Indices to Model Misspecified Structural or Measurement Model
  • Components: Rationale of Two-Index Strategy Revisited”, Structural Equation Modeling: A Multidisciplinary Journal, 12, 3: 343-367. FAN, X. and SİVO, S.A. (2007). “Sensitivity of Fit Indices to Model Misspecification and Model Types”,
  • Multivariate Behavioral Research, 42,3: 509-529. FAN, Xitao and FAN, Xiaotao (2005). “Using SAS for Monte Carlo Simulation Research in SEM”, Structural
  • Equation Modeling, 12, 2: 299-333. GERBİNG, D. W. and ANDERSON, J. C. (1993). “Monte Carlo Evaluation of Goodness-of-Fit Indices for
  • Structural Equation Models”, Testing Structural Equation Models, K. A. Bollen and J. S. Long (Eds.), Newport Beach, CA: Sage, 40-65. GOLOB, T.F. (2003). “Structural Equation Modeling for Travel Behavior Research”, Transportation Research Part B: Methodological, 37: 1-25.
  • HU, L. and BENTLER, P. M. (1998). “Fit Indices in Covariance Structure Modeling: Sensitivity to Under
  • Parameterized Model Misspecification”, Psychological Methods, 3: 424-453. HU, L. and BENTLER, P. M. (1999). “Cutoff Criteria for Fit Indexes in Covariance Structure Analysis:
  • Conventional Criteria Versus New Alternatives”, Structural Equation Modeling, 6: 1-55. KAPLAN, D. (2000). Structural Equation Modelling: Foundations and Extensions. Newbury Park, CA: Sage Publications.
  • KLİNE, B. R. (2005). Principles and Practice of Structural Modeling. New York, London: The Guilford Press.
  • LA DU, T. J. and TANAKA, J. S. (1989). “Influence of Sample Size, Estimation Method, and Model Specification on Goodness-of-Fit Assessments in Structural Equation Models”, Journal of Applied Psychology, 74, 4: 625-635.
  • LEİ, M. and LOMAX, R. G. (2005). “The Effect of Varying Degrees of Nonnormality in Structural Equation
  • Modeling”, Structural Equation Modeling: A Multidisciplinary Journal, 12, 1: 1-27. MACCALLUM, R. C., WEGENER, D. T., UCHİNO, B. N. and FABRİGAR, L. R. (1993). “The Problem of
  • Equivalent Models in Applications of Covariance Structure Analysis”, Psychological Bulletin, 114: 185-199. MAHLER, C. (2011). The Effects of Misspecifcation Type and Nuisance Variables on The Behaviors of Population
  • Fit İndices Used in Structural Equation Modeling. B.A: The University of British Columbia. MARSH, H. W., BALLA, J. R. and MCDONALD, R. P. (1988). “Goodness-of-Fit Indexes in Confirmatory Factor
  • Analysis: The Effect of Sample Size”, Psychological Bulletin, 103: 391-410. MARSH, H. W., BALLA J. R. and HAU, K. T. (1996). “An Evaluation of Incremental Fit Indices: A Clarificaation of Mathematical and Empirical Proporties”, Advanced Structural Equation Modeling: Issues and Techniques, G.A.
  • Marcoulides and R.E. Schumacker (Eds.) Erlbaum: Mahwah, NJ, 315-353. MARSH, H. W., HAU, K. T. and WEN, Z. (2004). “In Search of Golden Rules: Comment on Hypothesis-Testing
  • Approaches to Setting Cutoff Values for Fit Indexes and Dangers in Overgeneralizing Hu And Bentler’s (1999)
  • Findings”, Structural Equation Modeling, 11: 320-341. MULAİK, S. A., JAMES L. R., VAN ALSTİNE, J., BENNETT, N., LİND, S. and STİLWELL C. D. (1989).
  • “Evaluation of Goodness-of-Fit Indices for Structural Equation Models”, Psychological Bulletin, 105, 3: 430-445. OLSSON, U. H., FOSS, T., TROYE S. V. and HOWELL, R. D. (2000). “The Performance of ML, GLS, and WLS
  • Estimation in Structural Equation Modeling Under Conditions of Misspecification and Nonnormality”, Structural Equation Modeling: A Multidisciplinary Journal, 7, 4: 557-595. PAXTON, P., CURRAN, P.J., BOLLEN, K.A., KİRBY, J. and CHEN, F. (2001). “Monte Carlo Experiments: Design and Implementation”, Structural Equation Modeling: A Multidisciplinary Journal, 8, 2: 287-312.
  • RAYKOV, T. and MARCOULİDES, G. A. (2006). A First Course in Structural Equation Modeling. Lawrence
  • Erlbaum Associates, Mahlah-New Jersey-London: Lawrence Erlbaum Associates. SCHERMELLEH-ENGEL, K., MOOSBRUGGER, H. and MÜLLER, H. (2003). “Evaluating the Fit of Structural
  • Equation Models: Tests of Significance and Descriptive Goodness-of-Fit Measures”, Methods of Psychological Research Online, 8, 2: 23-74. SHARMA, S. (1996). Applied Multivariate Techniques. Inc: John Wiley and Sons.
  • SİVO, S. A., FAN, X., WİTTA, E. L. and WİLLSE, J. (2006). “The Search for "optimal" Cutoff Properties: Fit Index
  • Criteria in Structural Equation Modeling”, Journal of Experimental Education, 74, 3: 267-288. TANAKA, J. S. (1993). “Multifaceted Conceptions of Fit in Structural Equation Models”. In K.A. Bollen and J.S.
  • Long (Eds.), Testing Structural Equation Models (pp. 136-162). Newbury Park, CA: Sage. ULLMAN, J. B. (2001). “Structural Equation Modeling”, B.G. Tabachnick, L.S. Fidell, Using Multivariate
  • Statistics, 4th Edition, Needham Heights, MA: Allyn & Bacon, 653- 771. WENG, L-J. and CHENG C‐P. (1997). “Why Might Relative Fit Indices Differ Between Estimators?”, Structural
  • Equation Modeling: A Multidisciplinary Journal, 4, 2, 121-128. YILMAZ, V. (2004). “Consumer Behaviour of Shopping Center Choice”, Social Behavior and Personality, 32, 8, 783-7
  • YU, C. and MUTHEN, B. (2002). “Evaluation of the Model Fit Indices for Latent Variable Models with Categorical and Continuous Outcomes”, Paper Presented at the Annual Meeting of the American Educational Research
  • Association, New Orleans, LA.

MODEL BELİRLEMESİ, ÖRNEKLEM HACMİ VE TAHMİN YÖNTEMİNİN YAPISAL EŞİTLİK MODELLERİ UYUM ÖLÇÜTLERİNE ETKİSİ

Year 2013, Issue: 38, - , 01.06.2013

Abstract

Yapısal Eşitlik modelleri (YEM), ortaya çıkışı 1970’lere dayanan yeni bir metottur. Birçok araştırmacı tarafından, psikolojide, sosyolojide, biyolojide, eğitim araştırmalarında, politik bilimlerde ve pazarlama araştırmalarında kullanılmaktadır. YEM gözlenen değişkenlerin lineer bileşimi olarak yazılabilen çok sayıda içsel ve dışsal gizil değişkeni birlikte ele alan bir modelleme yöntemidir. Bu yüzden, YEM araştırmalarında model uyumunun değerlendirilmesi zorlu bir konudur. YEM’de model uyumunun deneysel olarak değerlendirilmesi ve istatistiksel tahminlerin elde edilmesinde Monte Carlo (MC) simülasyonu yaygın olarak kullanılmaya başlanmıştır. Bu çalışmada, model belirlemesinin, örneklem hacminin ve tahmin yönteminin YEM’de kullanılan uyum ölçütlerine etkisi, bir MC simülasyonu düzenlenerek araştırılmıştır

References

  • BEARDEN, W.O., SHARMA, S. and TEEL, J. E. (1982). “Sample Size Effects on Chi Square and Other Statistics
  • Used in Evaluating Causal Models”, Journal of Marketing Research, 19: 425-430. BENTLER, P.M. and BONETT, D.G. (1980). “Significance Tests and Goodness of Fit in the Analysis of Covariance
  • Structures”, Psychological Bulletin, 88, 3: 588-606. BENTLER, P. M. (1990). “Comperative Fit Index in Structural Models”, Psychogical Bulletin, 10, 2: 238-246.
  • BOLLEN, K. A. (1989). Structural Equations with Latent Variables. New York: Wiley.
  • ENDERS, C. and FİNLEY, S. (2003). “SEM Fit Index Criteria Re-Examined: An Investigation of ML And Robust
  • Fit Indices in Complex Models”, Paper presented at the annual meeting of the American Educational Research Association, Chicago. FAN, X. and WANG, L. (1998). “Effects of Potantial Confounding Factors on Fit Indices and Parameter Estimates for True and Misspesified SEM Models”, Educational and Psychological Measurement, 58: 699-733.
  • FAN, X., THOMPSON, B. and WANG, L. (1999). “Effects of Sample Size, Estimation Methods, and Model
  • Specification on Structural Equation Modeling Fit Indexes”, Structural Equation Modeling: A Multidisciplinary Journal, 6, 1: 56-83. FAN, X. and SİVO, S.A. (2005). “Sensitivity of Fit Indices to Model Misspecified Structural or Measurement Model
  • Components: Rationale of Two-Index Strategy Revisited”, Structural Equation Modeling: A Multidisciplinary Journal, 12, 3: 343-367. FAN, X. and SİVO, S.A. (2007). “Sensitivity of Fit Indices to Model Misspecification and Model Types”,
  • Multivariate Behavioral Research, 42,3: 509-529. FAN, Xitao and FAN, Xiaotao (2005). “Using SAS for Monte Carlo Simulation Research in SEM”, Structural
  • Equation Modeling, 12, 2: 299-333. GERBİNG, D. W. and ANDERSON, J. C. (1993). “Monte Carlo Evaluation of Goodness-of-Fit Indices for
  • Structural Equation Models”, Testing Structural Equation Models, K. A. Bollen and J. S. Long (Eds.), Newport Beach, CA: Sage, 40-65. GOLOB, T.F. (2003). “Structural Equation Modeling for Travel Behavior Research”, Transportation Research Part B: Methodological, 37: 1-25.
  • HU, L. and BENTLER, P. M. (1998). “Fit Indices in Covariance Structure Modeling: Sensitivity to Under
  • Parameterized Model Misspecification”, Psychological Methods, 3: 424-453. HU, L. and BENTLER, P. M. (1999). “Cutoff Criteria for Fit Indexes in Covariance Structure Analysis:
  • Conventional Criteria Versus New Alternatives”, Structural Equation Modeling, 6: 1-55. KAPLAN, D. (2000). Structural Equation Modelling: Foundations and Extensions. Newbury Park, CA: Sage Publications.
  • KLİNE, B. R. (2005). Principles and Practice of Structural Modeling. New York, London: The Guilford Press.
  • LA DU, T. J. and TANAKA, J. S. (1989). “Influence of Sample Size, Estimation Method, and Model Specification on Goodness-of-Fit Assessments in Structural Equation Models”, Journal of Applied Psychology, 74, 4: 625-635.
  • LEİ, M. and LOMAX, R. G. (2005). “The Effect of Varying Degrees of Nonnormality in Structural Equation
  • Modeling”, Structural Equation Modeling: A Multidisciplinary Journal, 12, 1: 1-27. MACCALLUM, R. C., WEGENER, D. T., UCHİNO, B. N. and FABRİGAR, L. R. (1993). “The Problem of
  • Equivalent Models in Applications of Covariance Structure Analysis”, Psychological Bulletin, 114: 185-199. MAHLER, C. (2011). The Effects of Misspecifcation Type and Nuisance Variables on The Behaviors of Population
  • Fit İndices Used in Structural Equation Modeling. B.A: The University of British Columbia. MARSH, H. W., BALLA, J. R. and MCDONALD, R. P. (1988). “Goodness-of-Fit Indexes in Confirmatory Factor
  • Analysis: The Effect of Sample Size”, Psychological Bulletin, 103: 391-410. MARSH, H. W., BALLA J. R. and HAU, K. T. (1996). “An Evaluation of Incremental Fit Indices: A Clarificaation of Mathematical and Empirical Proporties”, Advanced Structural Equation Modeling: Issues and Techniques, G.A.
  • Marcoulides and R.E. Schumacker (Eds.) Erlbaum: Mahwah, NJ, 315-353. MARSH, H. W., HAU, K. T. and WEN, Z. (2004). “In Search of Golden Rules: Comment on Hypothesis-Testing
  • Approaches to Setting Cutoff Values for Fit Indexes and Dangers in Overgeneralizing Hu And Bentler’s (1999)
  • Findings”, Structural Equation Modeling, 11: 320-341. MULAİK, S. A., JAMES L. R., VAN ALSTİNE, J., BENNETT, N., LİND, S. and STİLWELL C. D. (1989).
  • “Evaluation of Goodness-of-Fit Indices for Structural Equation Models”, Psychological Bulletin, 105, 3: 430-445. OLSSON, U. H., FOSS, T., TROYE S. V. and HOWELL, R. D. (2000). “The Performance of ML, GLS, and WLS
  • Estimation in Structural Equation Modeling Under Conditions of Misspecification and Nonnormality”, Structural Equation Modeling: A Multidisciplinary Journal, 7, 4: 557-595. PAXTON, P., CURRAN, P.J., BOLLEN, K.A., KİRBY, J. and CHEN, F. (2001). “Monte Carlo Experiments: Design and Implementation”, Structural Equation Modeling: A Multidisciplinary Journal, 8, 2: 287-312.
  • RAYKOV, T. and MARCOULİDES, G. A. (2006). A First Course in Structural Equation Modeling. Lawrence
  • Erlbaum Associates, Mahlah-New Jersey-London: Lawrence Erlbaum Associates. SCHERMELLEH-ENGEL, K., MOOSBRUGGER, H. and MÜLLER, H. (2003). “Evaluating the Fit of Structural
  • Equation Models: Tests of Significance and Descriptive Goodness-of-Fit Measures”, Methods of Psychological Research Online, 8, 2: 23-74. SHARMA, S. (1996). Applied Multivariate Techniques. Inc: John Wiley and Sons.
  • SİVO, S. A., FAN, X., WİTTA, E. L. and WİLLSE, J. (2006). “The Search for "optimal" Cutoff Properties: Fit Index
  • Criteria in Structural Equation Modeling”, Journal of Experimental Education, 74, 3: 267-288. TANAKA, J. S. (1993). “Multifaceted Conceptions of Fit in Structural Equation Models”. In K.A. Bollen and J.S.
  • Long (Eds.), Testing Structural Equation Models (pp. 136-162). Newbury Park, CA: Sage. ULLMAN, J. B. (2001). “Structural Equation Modeling”, B.G. Tabachnick, L.S. Fidell, Using Multivariate
  • Statistics, 4th Edition, Needham Heights, MA: Allyn & Bacon, 653- 771. WENG, L-J. and CHENG C‐P. (1997). “Why Might Relative Fit Indices Differ Between Estimators?”, Structural
  • Equation Modeling: A Multidisciplinary Journal, 4, 2, 121-128. YILMAZ, V. (2004). “Consumer Behaviour of Shopping Center Choice”, Social Behavior and Personality, 32, 8, 783-7
  • YU, C. and MUTHEN, B. (2002). “Evaluation of the Model Fit Indices for Latent Variable Models with Categorical and Continuous Outcomes”, Paper Presented at the Annual Meeting of the American Educational Research
  • Association, New Orleans, LA.
There are 37 citations in total.

Details

Primary Language Turkish
Journal Section Articles
Authors

Rana Şen This is me

Veysel Yılmaz This is me

Publication Date June 1, 2013
Published in Issue Year 2013 Issue: 38

Cite

APA Şen, R., & Yılmaz, V. (2013). MODEL BELİRLEMESİ, ÖRNEKLEM HACMİ VE TAHMİN YÖNTEMİNİN YAPISAL EŞİTLİK MODELLERİ UYUM ÖLÇÜTLERİNE ETKİSİ. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi(38).
AMA Şen R, Yılmaz V. MODEL BELİRLEMESİ, ÖRNEKLEM HACMİ VE TAHMİN YÖNTEMİNİN YAPISAL EŞİTLİK MODELLERİ UYUM ÖLÇÜTLERİNE ETKİSİ. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi. June 2013;(38).
Chicago Şen, Rana, and Veysel Yılmaz. “MODEL BELİRLEMESİ, ÖRNEKLEM HACMİ VE TAHMİN YÖNTEMİNİN YAPISAL EŞİTLİK MODELLERİ UYUM ÖLÇÜTLERİNE ETKİSİ”. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, no. 38 (June 2013).
EndNote Şen R, Yılmaz V (June 1, 2013) MODEL BELİRLEMESİ, ÖRNEKLEM HACMİ VE TAHMİN YÖNTEMİNİN YAPISAL EŞİTLİK MODELLERİ UYUM ÖLÇÜTLERİNE ETKİSİ. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi 38
IEEE R. Şen and V. Yılmaz, “MODEL BELİRLEMESİ, ÖRNEKLEM HACMİ VE TAHMİN YÖNTEMİNİN YAPISAL EŞİTLİK MODELLERİ UYUM ÖLÇÜTLERİNE ETKİSİ”, Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, no. 38, June 2013.
ISNAD Şen, Rana - Yılmaz, Veysel. “MODEL BELİRLEMESİ, ÖRNEKLEM HACMİ VE TAHMİN YÖNTEMİNİN YAPISAL EŞİTLİK MODELLERİ UYUM ÖLÇÜTLERİNE ETKİSİ”. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi 38 (June 2013).
JAMA Şen R, Yılmaz V. MODEL BELİRLEMESİ, ÖRNEKLEM HACMİ VE TAHMİN YÖNTEMİNİN YAPISAL EŞİTLİK MODELLERİ UYUM ÖLÇÜTLERİNE ETKİSİ. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi. 2013.
MLA Şen, Rana and Veysel Yılmaz. “MODEL BELİRLEMESİ, ÖRNEKLEM HACMİ VE TAHMİN YÖNTEMİNİN YAPISAL EŞİTLİK MODELLERİ UYUM ÖLÇÜTLERİNE ETKİSİ”. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, no. 38, 2013.
Vancouver Şen R, Yılmaz V. MODEL BELİRLEMESİ, ÖRNEKLEM HACMİ VE TAHMİN YÖNTEMİNİN YAPISAL EŞİTLİK MODELLERİ UYUM ÖLÇÜTLERİNE ETKİSİ. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi. 2013(38).

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