BibTex RIS Kaynak Göster

-

Yıl 2014, Cilt: 5 Sayı: 2, 26 - 42, 09.07.2014
https://doi.org/10.21031/epod.31126

Öz

This study aimed to compare the analysis results obtained through LISREL and AMOS for the models of path analysis, Confirmatory Factor Analysis (CFA) and structural regression, which are within structural equation model and differ in levels of fit. Therefore, population and sample were not needed in the study. The study was conducted on three different data sets that reflected the models through a data file. The data set used in the path analysis was determined to reflect a low fit model, while the one used in CFA was determined to reflect an acceptable fit model. However, the data set used in the structural model reflected a good fit. In this way, it was believed that it would be possible to find an answer to the question of whether the differences in the fit indexes obtained through LISREL and AMOS were affected by the fit level of the model analyzed. The analysis results indicated that the fit indexes obtained through LISREL and AMOS were substantially similar in the data set that reflected a good fit. The differences in the fit indexes obtained through these two software packages were found to be larger in the model that reflected a low fit between the model and the data set. It was also found that this difference was remarkable, particularly in χ2/sd, NNFI and RFI indexes. These results indicate that the differences in the fit indexes reported by LISREL and AMOS are affected by the fit level of the model

Kaynakça

  • Albright, J.J. & Park, H.M. (2008). Confirmatory Factor Analysis Using AMOS, LISREL, Mplus and SAS/STAT CALIS. Technical Working Paper: Indiana University.
  • Arbuckle, J. & Wothke, W. (1999). AMOS User’s Guide. Chicago, IL: Small Waters.
  • Arminger, G. (1997). MECOSA 3. Behaviormetrika, 24(1), 102-104.
  • Bagozzi, R.P. & Heatherton, T.F. (1994). A General Approach to Representing Multifaceted Personality Constructs: Application to State Self -Esteem. Structual Equation Model, 1(1), 35-67.
  • Bagozzi, R.P. & Yi, Y. (1988). On the Evaluation of Structural Equation Models. Journal of the Academy of Marketing Science, 16(1), 74-94.
  • Baumgartner, H. & Homburg, C. (1996). Applications of Structural Equation Modeling in Marketing and Consumer Research: A Review. International Journal of Research in Marketing, 13(2), 139-161.
  • Bayram, N. (2010). Yapısal Eşitlik Modellemesine Giriş AMOS Uygulamaları. İstanbul: Ezgi Kitabevi.
  • Bentler, P.M. (1980). Multivariate Analysis with Latent Variables: Causal Modeling. Annual Review of Psychology, 31, 419-456.
  • Bentler, P. M. (2004). EQS Structural Equations Program Manual. Encino, CA: Multivariate Software, Inc.
  • Bentler, P.M., & Bonett, D.G. (1980). Significance Tests and Goodness of Fit in the Analysis of Covariance Structures. Psychological Bulletin, 88, 588-606.
  • Bentler, P.M. & Yuan, K.H. (1999). Structural Equation Modeling with Small Samples: Test Statistics. Multivariate Behavioral Research, 34(2), 181-197.
  • Boker, S., Neale, M., Maes, H., Wilde, M., Spiegel, M.,
  • Brick, T. vd. (2011). OpenMx: An Open Source Extended Structural Equation Modeling Framework. Psychometrika, 76, 306-317.
  • Bordens, K.S. & Abbott, B.B. (2011). Research Design and Methods: A Process Approach. New York: The McGraw-Hill Companies.
  • Brown, T.A. (2006). Confirmatory Factor Analysis for
  • Applied Research. New York: The Guilford Press.
  • Browne, M.W. & Cudeck, R. (1993). Alternative Ways of Assessing Model Fit. In: Bollen, K.A. & Long, J.S. (Eds.), Testing Structural Equation Models (pp. 136–162). Beverly Hills, CA: Sage
  • Browne, M.W. & Mels, G. (2000). Path Analysis: RAMONA. In Systat 10.0: Statistics II (pp. 233-291). Chicago: SPSS.
  • Byrne, B.M. (2001). Structural Equation Modeling With AMOS, EQS, and LISREL: Comparative Approaches to Testing for the Factorial Validity of a Measuring Instrument. International Journal of Testing, 1(1), 55-86.
  • Cheung, G.W. & Renswold, R.B. (2002). Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance, Structural Equation Modeling, A Multidisciplinary Journal, 9(2), 233-255.
  • Clayton, M.F. & Pett, M. A. (2008). AMOS versus LISREL: One Data Set, Two Analyses. Nursing Research, 57(4), 283-292.
  • Çokluk, Ö., Şekercioğlu, G. & Büyüköztürk, Ş. (2012). Sosyal Bilimler için Çok Değişkenli İstatistik: SPSS ve LISREL Uygulamaları. Ankara: Pegem Akademi Yayıncılık.
  • Ferrer, E. Hamagami, F. & McArdle, J.J. (2004). Modeling Latent Growth Curves With Incomplete Data Using Different Types of Structural Equation Modeling and Multilevel Software. Structural Equation Modeling, 11(3), 452-483.
  • Fraser, C. & McDonald, R.P. (1988). COSAN: Covariance Structure Analysis. Multivariate Behavioral Research, 23, 258-348.
  • Davey, A. & Savla, J. (2010). Statistical Power Analysis with Missing Data: A Structural Equation Modeling Aproach.
  • Garver, M.S. and Mentzer, J.T. (1999). Logistics Research Methods: Employing Structural Equation Modeling to Test for Construct Validity. Journal of Business Logistics, 20(1), 33-57.
  • Gerbing, D.W., & Anderson, J.C. (1992). Monte Carlo Evaluations of Goodness of Fit Indices for Structural Equation Models. Sociological Methods and Research, 21(2), 132-160.
  • Gerbing, D.W. & Anderson, J.C. (1985). The Effects of Sampling Error and Model Characteristics on Parameter Estimation for Maximum Likelihood Confirmatory factor analysis. Multivariate Behavioral Research, 20, 255−271.
  • Hair, J.F., Anderson, R.E., Tatham, R.L. & Black, W.C. (1998). Multivariate Data Analysis. Englewood Cliffs, New Jersey: Prentice Hall.
  • Hershberger, S.L. (2003): The Growth of Structural Equation Modeling: 1994-2001. Structural Equation Modeling: A Multidisciplinary Journal, 10(1), 35-46.
  • Hoe, S.L. (2008). Issues and Procedures in Adopting Structural Equation Modeling Technique. Journal of Aplied Quantitative Methods, 3(1), 76-83.
  • Hooper, D., Coughlan, J. & Mullen, M. (2008). Structural Equation Modelling: Guidelines for Determining Model Fit. Electronic Journal of Business Research Methods, 6(1), 53-60.
  • Hox, J.J. (1995). AMOS, EQS and LISREL for Windows: A Comparative Review. Structural Equation Modeling: A Multidisciplinary Journal, 2(1), 79-91.
  • Hox, J.J. & Bechger, T.M. (1998). An Introduction to Structural Equation Modeling. Family Science Review, 11, 354-373.
  • Hoyle, R. H. (1995). The Structural Equation Modeling Approach. In R.H. Hoyle (Ed.), Structural Equation Modeling: Concepts, Issues, and Applications (pp. 1–15). Thousand Oaks, CA: Sage.
  • 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), 1-55.
  • Iacobucci, D. (2010). Structural Equations Modeling: Fit Indices, Sample Size, and Advanced Topics. Journal of Consumer Psychology, 20, 90-98.
  • Jöreskog, K. & Sörbom, D. (2000). LISREL [Computer Software]. Lincolnwood, IL: Scientific Software, Inc.
  • Kahn, J.H. (2006). Factor Analysis in Counseling Psychology Research, Training, and Practice: Principles, Advances and Applications. The Counseling Psychologist, 34, 684-718.
  • Kline, R.B. (2011). Principles and Practice of Structural Equation Modeling. New York: The Guilford Press.
  • Leech, N. L. Barrett, K. C. & Morgan, G.A. (2005). SPSS for Intermediate Statistics; Use and Interpretation. Mahwah, NJ: Lawrence Erlbaum Associates.
  • L
  • ei, P.W. & Wu, Q. (2007). Introduction to Structural Equation Modeling: Issues and Practical Considerations. Educational Measurement: Issues and Practice, 26(3), 33-43.
  • Marsh, H.W., Hau, K. T., Artelt, C., Baumert, J. & Peschar, J.L. (2006). OECD’s Brief Self-Report Measure of Educational Psychology’s Most Useful Affective Constructs: Cross-cultural, Psychometric Comparisons across 25 Countries. International Journal of Testing, 6(4), 311-360.
  • Meydan, C.H. & Şeşen, H. (2011). Yapısal Eşitlik Modellemesi ve AMOS Uygulamaları. Ankara: Detay Yayıncılık.
  • Mulaik, S.A. (2009). Linear Causal Modeling with Structural Equations. Boca Raton, FL: Chapman & Hall/CRC.
  • Mulaik, S.A., James, L.R., Alstine, J.A, Bennet, N., Lind, S. & Stilwell, C.D. (1989). Evaluation of Goodness-of-Fit Indices for Structural Equation Models. Psychological Bulletin, 105(3), 430-445.
  • Muthen, B.O. (1987). LISCOMP. Analysis of Linear Structural Equations with a Comprehensive Measurement Model. Theoretical Integration and User’s Guide. Mooresville, IN: Scientific Software.
  • Muthén, B.O. & Muthén, L. (2004). Mplus User’s Guide. Los Angeles, CA: Muthén& Muthén.
  • Neale, M. C., Boker, S.M., Xie, G. & Maes, H.H. (2004). Mx: Statistical Modeling. Richmond: Virginia Commonwealth University.
  • Pallant, J. (2005). SPSS Survival Manual: A Step by Step Guıde to Data Analysis Using SPSS for Wındows. Australia: Australian Copyright.
  • Pedhazur, E.J. (1997). Multiple Regression in Behavioral Research: Explanation and Prediction. New York: Holt, Rinehart & Winston.
  • Peprah, S. (2000). On Using AMOS, EQS, LISREL, Mx, RAMONA & SEPATH for Structural Equation Modeling. Unpublished Master Thesis, University of Port Elizabeth, Güney Afrika.
  • PROC CALIS. (2009). Computer Software Manual. Cary, SAS Institute, Inc.
  • Raykov, T. & Marcoulides, G.A. (2006). A First Course in Structural Equation Modeling. Mahwah, NJ: Lawrence Erlbaum.
  • Reisinger, Y. & Mavondo, F. (2007): Structural Equation Modeling, Journal of Travel & Tourism Marketing, 21(4), 41-71.
  • Reisinger, Y. & Turner, L. (1999). Structural Equation Modeling with LISREL: Application in Tourism. Tourism Management, 20, 71-88.
  • Rossel, Y. (2012). Iavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36.
  • Schermelleh-Engel, K. & Moosbrugger, 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.
  • Schoenberg, R. & Arminger, G. (1988). LINCS 2: A program for Linear Covariance Structure Analysis. Kensington MD: RJS Software.
  • Schreiber, B., Stage, F.K., King, J., Nora, A. & Barlow, E.A. (2006). Reporting Structural Equation Modeling and Confirmatory Factor Analysis Results: A Review. Journal of Educational Research, 99(6), 323-337.
  • Schumacker R.E. & Lomax R.G. (2004). A Beginner's Guide to Structural Equation Modeling. Mahwah, New Jersey: Lawrence Erlbaum Associates, Inc.
  • Steiger, J.H. (1994). SEPATH-A Statistica for Windows Structural Equation Modeling Program. In F. Faulbaum (Eds), Softstat '93: Advances in Statistical Software 4 (pp. 99-105). Stuttgart: Gustav Fischer Verlag.
  • Stevens, J.P. (2009). Applied Multivariate Statistics for the Social Sciences. New York: Routledge.
  • Sümer, N. (2000). Yapısal Eşitlik Modelleri: Temel Kavramlar ve Örnek Uygulamalar. Türk Psikoloji Yazıları, 3(6), 49-74.
  • Şimşek, Ö.F. (2007). Yapısal Eşitlik Modellemesine Giriş: Temel İlkeler ve LISREL Uygulamaları. Ankara: Ekinoks Yayınları.
  • Tabachnick, B.G. & Fidell, L.S. (2007). Using Multivariate Statistics. Boston, Pearson Education, Inc.
  • Ullman, J.B. (2001). Structural Equation Modeling. In B.G. Tabachnick & L.S. Fidell (Eds.), Using Multivariate Statistics. Needham Heights, MA: Allyn & Bacon.
  • Wetson, R. & Gore Jr, P.A. (2006). A Brief Guide to Structural Equation Model. The Counseling Psychologist, 34(5), 719-751.
  • Widaman, K.F. & Thompson, J.S. (2003). On Specifying the Null Model for Incremental Fit Indices in Structural Equation Modeling. Psychological Methods, 8(1), 16-37.
  • Yılmaz, V. & Çelik, H.E. (2009). LISREL ile Yapısal Eşitlik Modellemesi-I Temel Kavramlar, Uygulamalar, Programlama. Ankara: Pegem Akdemi Yayınları.

LISREL ve AMOS Programları Kullanılarak Gerçekleştirilen Yapısal Eşitlik Modeli (YEM) Analizlerine İlişkin Sonuçların Karşılaştırılması

Yıl 2014, Cilt: 5 Sayı: 2, 26 - 42, 09.07.2014
https://doi.org/10.21031/epod.31126

Öz

Bu araştırmada, yapısal eşitlik modeli çatısı altında yer alan ve uyum düzeyleri açısından farklılık gösteren yol analizi, Doğrulayıcı Faktör Analizi (DFA) ile yapısal regresyon modelleri için LISREL ve AMOS programlarından elde edilen analiz çıktılarının karşılaştırılması amaçlanmıştır. Dolayısıyla, araştırmada evren ve örneklem tayinine ihtiyaç duyulmamıştır. Araştırma; her bir modeli yansıtan bir veri dosyası olmak üzere üç ayrı bir veri seti üzerinden yürütülmüştür. Yol analizinde kullanılan veri seti düşük uyum gösteren bir model; DFA’da kullanılan veri seti kabul edilebilir uyum gösteren bir model ve yapısal regresyon modelinde kullanılan veri seti mükemmel uyum gösteren bir model olarak belirlenmiştir. Bu şekildeki bir yaklaşımın, LISREL ve AMOS programlarından elde edilen uyum indeksleri arasındaki farkın analiz edilen modelin uyum düzeyinden etkilenip etkilenmediği sorusunu yanıtlamayı olanaklı hale getireceği düşünülmüştür. Analiz çıktıları incelendiğinde; model uyumunun mükemmel olduğu veri setinde LISREL ve AMOS programından elde edilen uyum indekslerinin büyük ölçüde eş değer olduğu belirlenmiştir. Model ile veri seti arasındaki uyumunun düşük olduğu modelde ise, iki programda rapor edilen uyum indeksleri arasındaki farkın daha fazla olduğu saptanmıştır. Bu farkın, özellikle, χ2/sd, NNFI ve RFI indeksleri için belirgin olduğu sonucuna ulaşılmıştır. Bu sonuçlar; LISREL ve AMOS programlarında rapor edilen uyum indeksleri arasındaki farkın modelin uyum düzeyinden etkilendiğini ortaya koymaktadır.

Kaynakça

  • Albright, J.J. & Park, H.M. (2008). Confirmatory Factor Analysis Using AMOS, LISREL, Mplus and SAS/STAT CALIS. Technical Working Paper: Indiana University.
  • Arbuckle, J. & Wothke, W. (1999). AMOS User’s Guide. Chicago, IL: Small Waters.
  • Arminger, G. (1997). MECOSA 3. Behaviormetrika, 24(1), 102-104.
  • Bagozzi, R.P. & Heatherton, T.F. (1994). A General Approach to Representing Multifaceted Personality Constructs: Application to State Self -Esteem. Structual Equation Model, 1(1), 35-67.
  • Bagozzi, R.P. & Yi, Y. (1988). On the Evaluation of Structural Equation Models. Journal of the Academy of Marketing Science, 16(1), 74-94.
  • Baumgartner, H. & Homburg, C. (1996). Applications of Structural Equation Modeling in Marketing and Consumer Research: A Review. International Journal of Research in Marketing, 13(2), 139-161.
  • Bayram, N. (2010). Yapısal Eşitlik Modellemesine Giriş AMOS Uygulamaları. İstanbul: Ezgi Kitabevi.
  • Bentler, P.M. (1980). Multivariate Analysis with Latent Variables: Causal Modeling. Annual Review of Psychology, 31, 419-456.
  • Bentler, P. M. (2004). EQS Structural Equations Program Manual. Encino, CA: Multivariate Software, Inc.
  • Bentler, P.M., & Bonett, D.G. (1980). Significance Tests and Goodness of Fit in the Analysis of Covariance Structures. Psychological Bulletin, 88, 588-606.
  • Bentler, P.M. & Yuan, K.H. (1999). Structural Equation Modeling with Small Samples: Test Statistics. Multivariate Behavioral Research, 34(2), 181-197.
  • Boker, S., Neale, M., Maes, H., Wilde, M., Spiegel, M.,
  • Brick, T. vd. (2011). OpenMx: An Open Source Extended Structural Equation Modeling Framework. Psychometrika, 76, 306-317.
  • Bordens, K.S. & Abbott, B.B. (2011). Research Design and Methods: A Process Approach. New York: The McGraw-Hill Companies.
  • Brown, T.A. (2006). Confirmatory Factor Analysis for
  • Applied Research. New York: The Guilford Press.
  • Browne, M.W. & Cudeck, R. (1993). Alternative Ways of Assessing Model Fit. In: Bollen, K.A. & Long, J.S. (Eds.), Testing Structural Equation Models (pp. 136–162). Beverly Hills, CA: Sage
  • Browne, M.W. & Mels, G. (2000). Path Analysis: RAMONA. In Systat 10.0: Statistics II (pp. 233-291). Chicago: SPSS.
  • Byrne, B.M. (2001). Structural Equation Modeling With AMOS, EQS, and LISREL: Comparative Approaches to Testing for the Factorial Validity of a Measuring Instrument. International Journal of Testing, 1(1), 55-86.
  • Cheung, G.W. & Renswold, R.B. (2002). Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance, Structural Equation Modeling, A Multidisciplinary Journal, 9(2), 233-255.
  • Clayton, M.F. & Pett, M. A. (2008). AMOS versus LISREL: One Data Set, Two Analyses. Nursing Research, 57(4), 283-292.
  • Çokluk, Ö., Şekercioğlu, G. & Büyüköztürk, Ş. (2012). Sosyal Bilimler için Çok Değişkenli İstatistik: SPSS ve LISREL Uygulamaları. Ankara: Pegem Akademi Yayıncılık.
  • Ferrer, E. Hamagami, F. & McArdle, J.J. (2004). Modeling Latent Growth Curves With Incomplete Data Using Different Types of Structural Equation Modeling and Multilevel Software. Structural Equation Modeling, 11(3), 452-483.
  • Fraser, C. & McDonald, R.P. (1988). COSAN: Covariance Structure Analysis. Multivariate Behavioral Research, 23, 258-348.
  • Davey, A. & Savla, J. (2010). Statistical Power Analysis with Missing Data: A Structural Equation Modeling Aproach.
  • Garver, M.S. and Mentzer, J.T. (1999). Logistics Research Methods: Employing Structural Equation Modeling to Test for Construct Validity. Journal of Business Logistics, 20(1), 33-57.
  • Gerbing, D.W., & Anderson, J.C. (1992). Monte Carlo Evaluations of Goodness of Fit Indices for Structural Equation Models. Sociological Methods and Research, 21(2), 132-160.
  • Gerbing, D.W. & Anderson, J.C. (1985). The Effects of Sampling Error and Model Characteristics on Parameter Estimation for Maximum Likelihood Confirmatory factor analysis. Multivariate Behavioral Research, 20, 255−271.
  • Hair, J.F., Anderson, R.E., Tatham, R.L. & Black, W.C. (1998). Multivariate Data Analysis. Englewood Cliffs, New Jersey: Prentice Hall.
  • Hershberger, S.L. (2003): The Growth of Structural Equation Modeling: 1994-2001. Structural Equation Modeling: A Multidisciplinary Journal, 10(1), 35-46.
  • Hoe, S.L. (2008). Issues and Procedures in Adopting Structural Equation Modeling Technique. Journal of Aplied Quantitative Methods, 3(1), 76-83.
  • Hooper, D., Coughlan, J. & Mullen, M. (2008). Structural Equation Modelling: Guidelines for Determining Model Fit. Electronic Journal of Business Research Methods, 6(1), 53-60.
  • Hox, J.J. (1995). AMOS, EQS and LISREL for Windows: A Comparative Review. Structural Equation Modeling: A Multidisciplinary Journal, 2(1), 79-91.
  • Hox, J.J. & Bechger, T.M. (1998). An Introduction to Structural Equation Modeling. Family Science Review, 11, 354-373.
  • Hoyle, R. H. (1995). The Structural Equation Modeling Approach. In R.H. Hoyle (Ed.), Structural Equation Modeling: Concepts, Issues, and Applications (pp. 1–15). Thousand Oaks, CA: Sage.
  • 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), 1-55.
  • Iacobucci, D. (2010). Structural Equations Modeling: Fit Indices, Sample Size, and Advanced Topics. Journal of Consumer Psychology, 20, 90-98.
  • Jöreskog, K. & Sörbom, D. (2000). LISREL [Computer Software]. Lincolnwood, IL: Scientific Software, Inc.
  • Kahn, J.H. (2006). Factor Analysis in Counseling Psychology Research, Training, and Practice: Principles, Advances and Applications. The Counseling Psychologist, 34, 684-718.
  • Kline, R.B. (2011). Principles and Practice of Structural Equation Modeling. New York: The Guilford Press.
  • Leech, N. L. Barrett, K. C. & Morgan, G.A. (2005). SPSS for Intermediate Statistics; Use and Interpretation. Mahwah, NJ: Lawrence Erlbaum Associates.
  • L
  • ei, P.W. & Wu, Q. (2007). Introduction to Structural Equation Modeling: Issues and Practical Considerations. Educational Measurement: Issues and Practice, 26(3), 33-43.
  • Marsh, H.W., Hau, K. T., Artelt, C., Baumert, J. & Peschar, J.L. (2006). OECD’s Brief Self-Report Measure of Educational Psychology’s Most Useful Affective Constructs: Cross-cultural, Psychometric Comparisons across 25 Countries. International Journal of Testing, 6(4), 311-360.
  • Meydan, C.H. & Şeşen, H. (2011). Yapısal Eşitlik Modellemesi ve AMOS Uygulamaları. Ankara: Detay Yayıncılık.
  • Mulaik, S.A. (2009). Linear Causal Modeling with Structural Equations. Boca Raton, FL: Chapman & Hall/CRC.
  • Mulaik, S.A., James, L.R., Alstine, J.A, Bennet, N., Lind, S. & Stilwell, C.D. (1989). Evaluation of Goodness-of-Fit Indices for Structural Equation Models. Psychological Bulletin, 105(3), 430-445.
  • Muthen, B.O. (1987). LISCOMP. Analysis of Linear Structural Equations with a Comprehensive Measurement Model. Theoretical Integration and User’s Guide. Mooresville, IN: Scientific Software.
  • Muthén, B.O. & Muthén, L. (2004). Mplus User’s Guide. Los Angeles, CA: Muthén& Muthén.
  • Neale, M. C., Boker, S.M., Xie, G. & Maes, H.H. (2004). Mx: Statistical Modeling. Richmond: Virginia Commonwealth University.
  • Pallant, J. (2005). SPSS Survival Manual: A Step by Step Guıde to Data Analysis Using SPSS for Wındows. Australia: Australian Copyright.
  • Pedhazur, E.J. (1997). Multiple Regression in Behavioral Research: Explanation and Prediction. New York: Holt, Rinehart & Winston.
  • Peprah, S. (2000). On Using AMOS, EQS, LISREL, Mx, RAMONA & SEPATH for Structural Equation Modeling. Unpublished Master Thesis, University of Port Elizabeth, Güney Afrika.
  • PROC CALIS. (2009). Computer Software Manual. Cary, SAS Institute, Inc.
  • Raykov, T. & Marcoulides, G.A. (2006). A First Course in Structural Equation Modeling. Mahwah, NJ: Lawrence Erlbaum.
  • Reisinger, Y. & Mavondo, F. (2007): Structural Equation Modeling, Journal of Travel & Tourism Marketing, 21(4), 41-71.
  • Reisinger, Y. & Turner, L. (1999). Structural Equation Modeling with LISREL: Application in Tourism. Tourism Management, 20, 71-88.
  • Rossel, Y. (2012). Iavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36.
  • Schermelleh-Engel, K. & Moosbrugger, 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.
  • Schoenberg, R. & Arminger, G. (1988). LINCS 2: A program for Linear Covariance Structure Analysis. Kensington MD: RJS Software.
  • Schreiber, B., Stage, F.K., King, J., Nora, A. & Barlow, E.A. (2006). Reporting Structural Equation Modeling and Confirmatory Factor Analysis Results: A Review. Journal of Educational Research, 99(6), 323-337.
  • Schumacker R.E. & Lomax R.G. (2004). A Beginner's Guide to Structural Equation Modeling. Mahwah, New Jersey: Lawrence Erlbaum Associates, Inc.
  • Steiger, J.H. (1994). SEPATH-A Statistica for Windows Structural Equation Modeling Program. In F. Faulbaum (Eds), Softstat '93: Advances in Statistical Software 4 (pp. 99-105). Stuttgart: Gustav Fischer Verlag.
  • Stevens, J.P. (2009). Applied Multivariate Statistics for the Social Sciences. New York: Routledge.
  • Sümer, N. (2000). Yapısal Eşitlik Modelleri: Temel Kavramlar ve Örnek Uygulamalar. Türk Psikoloji Yazıları, 3(6), 49-74.
  • Şimşek, Ö.F. (2007). Yapısal Eşitlik Modellemesine Giriş: Temel İlkeler ve LISREL Uygulamaları. Ankara: Ekinoks Yayınları.
  • Tabachnick, B.G. & Fidell, L.S. (2007). Using Multivariate Statistics. Boston, Pearson Education, Inc.
  • Ullman, J.B. (2001). Structural Equation Modeling. In B.G. Tabachnick & L.S. Fidell (Eds.), Using Multivariate Statistics. Needham Heights, MA: Allyn & Bacon.
  • Wetson, R. & Gore Jr, P.A. (2006). A Brief Guide to Structural Equation Model. The Counseling Psychologist, 34(5), 719-751.
  • Widaman, K.F. & Thompson, J.S. (2003). On Specifying the Null Model for Incremental Fit Indices in Structural Equation Modeling. Psychological Methods, 8(1), 16-37.
  • Yılmaz, V. & Çelik, H.E. (2009). LISREL ile Yapısal Eşitlik Modellemesi-I Temel Kavramlar, Uygulamalar, Programlama. Ankara: Pegem Akdemi Yayınları.
Toplam 71 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Mustafa İlhan

Bayram Çetin

Yayımlanma Tarihi 9 Temmuz 2014
Yayımlandığı Sayı Yıl 2014 Cilt: 5 Sayı: 2

Kaynak Göster

APA İlhan, M., & Çetin, B. (2014). LISREL ve AMOS Programları Kullanılarak Gerçekleştirilen Yapısal Eşitlik Modeli (YEM) Analizlerine İlişkin Sonuçların Karşılaştırılması. Journal of Measurement and Evaluation in Education and Psychology, 5(2), 26-42. https://doi.org/10.21031/epod.31126

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