نمذجة المعادلة البنائية للعلوم النفسية والاجتماعية: الأسس والتطبيقات والقضايا (الجزء الثاني)

أولاً: المراجع العربية:

عامر، عبد الناصر السيد. (2004). أداء مؤشرات حسن المطابقة لتقويم نموذج المعادلة البنائية، المجلة المصرية للدراسات النفسية، مجلد 14.

عامر، عبد الناصر السيد.(2005). بنية نظرية توجه الهدف: استقلالية أم ارتباطية، المجلة المصرية للدراسات النفسية، 15، 278 – 309.

عامر، عبد الناصر السيد. (2007). حجم العينة في تحليل الانحدار المتعدد. المجلة المصرية للدراسات النفسية، المجلد 17.

عامر، عبد الناصر السيد. (2008). الدقة التنبؤية لدرجة اختبار القبول وتحصيل اللغة الفرنسية في الثانوية العامة للتنبؤ بتحصيل الجامعة لشعبة اللغة الفرنسية، مجلة كلية التربية ببنها، 18، 39-49.

عامر، عبد الناصر السيد. (2014a). تقويم استخدام تطبيقات نمذجة المعادلة البنائية في البحث النفسي. مجلة دراسات عربية في علم النفس(رانم)، 13، 701- 777.

عامر، عبد الناصر السيد. (2014b). نمذجة المعادلة البنائية الاستكشافية في مقابل التحليل العاملي التوكيدي للبنية الداخلية لأهداف الإنجاز. المجلة المصرية للدراسات النفسية، 24,404 -430.

عامر، عبد الناصر السيد. (2015). فحص تأثيرات الطريقة في مقياس تقدير الذات لروسينبرج: نماذج عاملية متنافسة. المجلة المصرية للدراسات النفسية،25 ، 1- 31.

عامر، عبد الناصر السيد. (2016). نمذجة المعادلة البنائية: بعض القضايا المنهجية والتوصيات. المجلة المصرية للدراسات النفسية، 26، 37-58.

ثانيًا: المراجع الأجنبية:

- Algina, J., & Olejnik, S. (2000). Determining sample size for Accurate Estimation of the squared Multiple correlation coefficient. Multivariate Behavioral Research, 35, 119 – 137.

- Anderson , J. C., & Gerbing, D. V. (1988). Structural equation modeling in practice: Areview and recommended two – step approach. Psychological Bulletin, 103, 411-423.

- Anderson, J. C., & Gerbing, D. W. (1992). Assumptions and comparative strength of the two – step approach: Comment on Fornell and YI. Sociological Methods & Research, 20, 321 – 333.

- Arrindel, W. A., & Van der Ende. J. (1985). An Empirical test of the utility of the observations to variables ratio of factor and component analysis. Applied Psychological Measurement, 9, 165-178

- Asparouhov, T., & Muthen, B. ( 2009 ). Exploratory Structural Equation Modeling. Structural Equation Modeling , 156, 397 – 438.

- Azen, R., Budescu, B. V., & Reisr, B. (2001). Criticality of predictors in multiple regression. British Journal of Mathematical and Statistical Psychology, 54, 201-225.

- Bagozzi, R. P. (1993). Assessing construct validity in personality research : Applications to measure of self – esteem . Journal of Research in personality, 27, 49 – 87.

- Bagozzi, R. P., & Heatherton, T. F. (1994). AGeneral approach to representing multifaceted personality constructs: Application to state self-esteem. Structural Equation Modeling, 1, 35-67.

- Bartlett, M. S. (1954). A note on the multiplying factors for various chi square approximations. Journal of the Royal Statistical Society, 16, 296-298.

- Baumgartner, H., & Homburg, C. (1996). Applications of structural equation modeling in marketing and consumer Research: A review. International Journal of Research in Marketing, 13, 139-161.

- Bentler , P . M. (2002). EQS 6: Structural equations program manual. Encino,CA: Multivariate Software , Inc..

- Bentler, P. M., & Chou, C. P. (1987). Practical issues in structural modeling. Sociological Methods and Research, 16, 78-117.

- Bollen, K. A. (1989). Structural equations with Latent variables. New York: Wiley.

- Boomsma, A. (2000). Reporting analysis covariance structure. Structural Equation Modeling, 7, 461- 483.

- Borkenau, P., & Ostendorf, F. ( 1990 ). Comparing exploratory and Confirmatory factor analysis : A study on the five factor model of personality . Personality and Individual Differences, 11, 515-524 .

- Breckler, S. T. (1990). Application of covariance structure modeling in psychology: Cause for concern? Psychological Bulletin, 107, 260 – 273.

- Brown, T. A. (2006). Confirmatory factor analysis for applied research. New York: Guilford Press.

- Browne, M.W. (1975). Comparison of single sample and cross-validation methods for estimating the mean squared error of prediction in multiple linear regression. British Journal of Mathematical and Statistical Psychology, 28, 112–120.

- Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Research, 1, 245-276.

- Chou, C. P., & Bentler, P. M. (1995). Estimates and tests in structural equation modeling. In. R. H. Hoyle (Eds.), Structural equation modeling : concepts, issues, and applications (PP. 37- 59). Thousand Oaks, CA: Sage.

- Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Mahwah, NJ: Erlbaum

- Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression / correlation analysis for behavioral sciences (3th.ed). Mahwah: Lawrence Erlbaum Associates, Publishers.

- Comery, A. L., & Lee, H. B. (1992). A First course in factor analysis (2nd .ed). Hillsadale, NJ: Erbaum.

- Costello, A. B., & Osborne, J. W. (2005). Best practices in exploratory factor analysis: Recommendations for getting the Most from your analysis. Practical Assessment, Research, and Evaluation, 10, 1-9.

- Cote , J . A ., & Buckley , R . (1987). Estimating trait , method and erro variance: Generalizing across to construct validation studies. Journal of Marketing Research , 24 , 315-318

- Cronbach, L. J. & Webb, N. ( 1979 ). Between class and within class effects in a reported aptitude and treatment interaction: A reanalysis of a study by G. L. Anderson . Journal of Educational Psychology , 79 , 717 – 724 .

- Deweck, C., & Legget, E. (1988). Asocial cognitive approach to motivation and personality. Psychological Review, 95, 256 – 273.

- Distefano, C., & Molt, R. W. ( 2006). Further investingation method effects associated with negatively worded items on self – reprot survey . Structures Equation Modeling , 123, 440 – 464.

- Dyer, N. G., Hanges, P. J., & Hall, R. J. (2005). Applying multilevel confirmatory factor analysis techniques to the study of leadership. The leadership Quarterly, 16, 149 – 167.

- Elliot, A., & Church, M. (1997). A hierarchical model of approach and avoidance achievement motivation. Journal of Personality and Social psychology, 72, 218 – 232.

- Elliot, A., & McGregor, H. A. (2001). 2  2 achievement goal framework. Journal of Personality and Social Psychology, 80, 501 – 519.

- Fabrigar, L. R.,Wegener, D. T., MacCullum, R. C., & Strahan, E. J. (1999). Evaluating the use of factor analysis in psychological research. Psychological Methods,4 ,272-299.

- Fava, J. L., & Velicer, W. F. (1992). The effects of over extraction on factor and component analysis. Multivariate Behavioral Research , 27,387-415.

- Field, A. (2009). Discovering statistics using SPSS(3th.ed). London: Sage publications, LTD.

- Green, S. B. (1991). How many subjects does it take to do regression analysis? Multivariate Behavioral Research, 27, 499-510.

- Gorsuch, R. L. (1983). Factor Analysis (2nd ed.). Hillsdale, NJ Lawrence Erlbaum Associates.

- Guadagnoli, E., & Velicer, W. F. (1988). Relation of sample size to the stability of component patterns. Psychological Bulletin, 103, 265-275.

- Guilford,J. P. (1954). Psychometric methods(2nd ed.). New York: McGraw-Hill.

- Hair Jr. J. H., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis. New Jersey: Prentice- Hall.

- Harris, R. J. (1975). A primer of multivariate statistics. New York: Academic.

- Heck, R. (2001). Multilevel modeling with SEM. IN F . Marcoulides & R. Schumacher (Eds.), New developments and techniques in structural equation modeling (pp. 89 – 127). Mahwahg, NJ: Lawrence Erlbaum Associates , Inc .

- Henson, R. K., & Roberts, J. K. (2006). Use of exploratory factor analysis in published research: Common errors and comment on improved. Educational and Psychological Measurement, 66,393-416.

- Holbert, R. L., & Stephenson, M. T. (2002). Structural equation modeling in communication sciences(1995- 2000). Human Communication Research, 28, 531-551.

- Howell, D. C. (2013). Statistics methods for psychology(8th.ed). Belmont: Wadsworth, Cengage Learning.

- Hox, J . J. (2010). Multilevel analysis: Techniques and applications . New York and Hove : Routledge .

- Hox, J . J ., & Kreft, I. G. G. (1994). Multilevel analysis models . Sociological Methods and Research , 22 , 283 – 299 .

- Hox, J. J., & Mass , C. J. M. (2001). The a ccuracy of multilevel structural equation modeling with pseudobalnced groups and small samples. Journal of Educational and Behavioral Statistics , 8 , 157 – 174 .

- Hoyle, R. H. (1995). Structural equation modeling: Basic concepts and fundamental issues .In R . H. Hoyle (Eds.),Structural equation modeling: Concepts, issues, and applications ( PP1-15 ). Thousand Oaks, CA: Sage.

- Hoyle, R. H, & Panter, A. T. (1995). Writing about structural equation modeling. In R. H. Hoyle (Eds.), Structural Equation Modeling: concepts, issues, and application (PP.158-175) .thousand Oaks: Sage.

- Hu, L., & Bentler, P. M. (1995). Evaluating model fit. In R. H. Hoyle (Eds.), Structural equation modeling: concepts, issues, and applications (PP. 76- 99). 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- 55.

- Hulland, J., Chow, Y. H., & Lam, S. (1996). Use of causal models in marketing research: A review. International. Journal. of Research in marketing, 13, 181-197.

- Jolliffe, I. (1972). Discarding Variables in a Principal Component Analysis. I: Artificial Data. Journal of the Royal Statistical Society. Series C (Applied Statistics), 21(2), 160-173.

- Kaiser, H. F. (1960). An index of factorial simplicity. Psychometrika, 35, 401-415.

- Kaplan, D., & Elliot, P. R. (1997). A model – based approach to validating educational indicators using multilevel structural equation modeling. Journal of Educational and Behavioral statistics , 22 , 323 – 347

- Keith, T. Z. (2014). Multiple regression and beyond: An introduction to multiple regression and structural equation modeling (2nd ed). New York: Routeledge.

- Kenny, D. A., & Kashy, D. A. Bolger (1998). Data analysis in social psychology. The Handbook of Social Psychology (4th Ed.). New York: McGraw-Hill.

- Kline, R. K. (2011). Principles and practice of structural equation modeling (3th.ed). New York: Guilford publications, Inc.

- Kline, R. K. (2016). Principles and practice of structural equation modeling (4th.ed). New York: Guilford publications, Inc.

- Kromrey, J. D. & Hines, C. V. (1996). Estimation the coefficient of cross validity in multiple regression: A comparison of Analytical and Empirical Methods. The Journal of Experimental Education, 64, 240-266.

- MacCallum, R. C, & Austin, J. T. (2000). Application of structural equation modeling in psychological research. Annual Review of Psychology, 51, 201-226.

- Mallow, C. L. (1973). Some comments on Cp. Technometrics, 15, 661-675.

- Marsh, H. W. ( 1983 ). Multi - dimensional ratings of teaching effectiveness by student from different academic settings and their relation to student instructor characteristics . Journal of Educational Psychology ,75 , 150-166.

- Marsh, H. W. ( 1996 ). Positive and negative global self – esteem: A substantively meaningful distinction or art: factors ? Journal of Personality and Social Psychology , 70 , 810-819.

- Marsh, H . W., Hau, T., & Grayson . D. (2005). Goodness of fit evaluation in structural equation modeling . In A. Mayday – Olivares & J . McCardle (eds.), Psychometrics : A festschrift to Roderick P. McDonald (PP. 275-340 ). Mahwah, NJ: Lawrence Erlbaum Associates, INC.

- Marsh, H. W., Liem, G. A. D, Martin, A . J., Morin, A. J. S., & Nagengast, B. (2011). Methodological measurement fruitfulness of exploratory structural equation modeling (ESEM) : New approaches to key substantive issues in motivation and engagement . Journal of Psychoeducational Assessment, 29 , 322 – 346 .

- Marsh, H. W., Muthen, B., Asparouhov, T., Ludtke, O., Robitzsch, A., Morin, A. J. S., & Trautwein, U. (2009). Exploratory structural equation modeling : Integrating CFA and EFA : Applications to student's evaluations of university teaching . Structural Equation Modeling , 16 , 439 – 476 .

- Martines, M. P. (2005). The use of structural equation modeling in counseling psychology research. The Counseling Psychologist, 33, 269- 298.

- McCrae, R. R., Zonderman, A. B., Costa, P. T., Bond, M. H., & Paunonen, S. V. (1996). Evaluating replicaility of factors in the revised NEO personality inventory: Confirmatory factor analysis versus procrustean rotation. Journal of Personality and Social Psychology,70 , 552 – 566.

- McDonald, R. P., & Ho, M. R. (2000). Principles and practice of reporting structural equation modeling. Psychological Methods, 7, 64- 82.

- Middleton, M., & Midgley, C. (1997). Avoiding the demonstration of lack of ability: An under – explored aspect of goal theory. Journal of Educational Psychology, 89, 710- 718.

- Moerbeek, M. (2004 ). The Consequence of ignoring a level of nesting in multilevel analysis. Multivariate Behavioral Research, 39, 129 – 149.

- Mok, M. (1995) . Sample size requirements for level designs in educational research. Australia. Sydney: Macquarie university.

- Morin, A. J., & Maiano, C. (2011). Cross – validation of the short form of the physical self – inventory (PSI- S) using exploratory Structural Equation Modeling(ESEM). Psychology of Sport and Exercise, 12, 540 – 554.

- Mote,T. A. (1970). An artifact of the rotation of too few factors: Study orientation VS. trait anxiety. Revista Interamericana De Psicologia,37,267-305.

- Mulaik, S. A. (1990). Blurring the distinctions between component analysis and common factor analysis. Multivariate Behavioral Research, 25, 53-59.

- Muthen. B. (1984). A general structural equation model with dichotomous, ordered categorical and continuous latent variable indicators. Psychometrika , 49, 15-132 .

- Muthen, B. O. (1990 ). Mean and covariance structure analysis of hierarchical data . Paper presented at the Psychometric Society , New Jewsy : Princeton .

- Muthen, B. O. (1991). Multilevel factor analysis of class and student achievemt components. Journal of Educational Measurement , 28 , 338 – 354.

- Muthen, B. O. (1994). Multilevel covariance structure analysis. Sociological Methods and Research , 22, 376-398.

- Muthén, L. K., & Muthén, B. O. (2002). How to use a Monte Carlo study to decide on sample size and determine power. Structural Equation Modeling, 4, 599-620.

- Muthén, L., & Muthen, B.O. (1998-2010). Mplus User’s Guide, (6th Ed.).Muthén and Muthén, Los Angeles. CA, USA.

- Myers, N. D. (2013). Coaching Competency and (exploratory) Structural equation modeling: A substantive – methodological synergy. Psychology of Sport and Exercise,14, 709 – 718.

- Nunkoo, R., Ramkissom, H., & Gursoy, D. (2013). Use of structural equation modeling in tourism research: Past, present, and future. Journal of Travel Research, xxx, 1-13.

- Nunnaly, J. C. (1978). Psychometric theory. New York: McGraw-Hill.

- Olejnik, S., Mills, J., & Keselman, H. (2000). Using wherry’s adjusted R2 and Mallow’s Cp for Model selection from all possible Regression. The Journal of Experimental Education, 68, 365-380.

- Pedhazure, E. J. (1997). Multiple regressions in behavioral research: Explanation and prediction(3rd ed). Australia: Wadsworth.

- Podsakoff, P. M., Mackenzie, S. B., lee, J. Y., & podsakoff , N. P. ( 2003 ).Common method biases in behavioral research: A critical review of literature and recommended remdies . Journal of Applied Psychology , 88, 879 – 903 .

- Raju, N. S., Bilgic, R., Edwards, J. E., & Fleer, P. F. (1999). Accuracy of population validity and cross-validity Estimation: An empirical comparison of formula-based traditional empirical and Equal weights procedures. Applied Psychological Measurement, 23, 99-115.

- Raykov, T., & Marcoulides, G. A. (2006). A first course in structural equation modeling (2nd. ed). New Jersey: Erlbaum.

- Raykov, T., Tomer, A., & Nesselroade. J. R. (1991). Reporting structural equation modeling results in psychology and aging: some proposed guidelines. Psychology and Aging, 6, 499 – 503.

- Rosenberg, M. (1965). Socity and adolescents self image. Princeton, N J: Prinction university.

- Rosenberg, S. L. (2009). Multilevel validity : Assessing the validity of school – level inference from student Achievement test Data . A dissertation of Doctor philosophy , school of education , Chapel Hill , USA.

- Sass, D. A., & Schmitt, T. A. (2010). A Comparative investigation of rotation criteria within exploratory factor analysis . Multivariate Behavioral Research , 45, 73-103 .

- Satorra, A., & Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. Von Eye & C. C. Clogg (Eds.), Latent variable analysis: Applications for development research. Thousand Oaks, CA: Sage.

- Schreiber, J. B., Stage, F. K., king, k., Nora, A., & Barlow, E.A. (2006). Reporting structural equation modeling and confirmatory factor analysis results: A Review. The Journal of Education Research, 99, 323-337.

- Schumacker, R. E., & Lomax, R. G. (1996). Beginner’s guide to structural equation modeling. Mahwah, NJ: Lawrence Erlbaum.

- Schumacker, R. E., & Lomax, R. G. (2010). Beginner’s guide to structural equation modeling (3rd ed). Mahwah, NJ: Lawrence Erlbaum.

- Shah, R., & Goldstein, S. M. (2006). Use of structural equation modeling in operations management research: Looking back and forward. Journal of Operation Management, 24, 148-169.

- Shook, C. L., Ketchen D. J., Hult, G. T. M., & Kacmar, K. M. (2004). An assessment of the use of structural equation modeling in strategic management Research. Strategic Management Journal, 25, 397 -404.

- Smith, d., & Smith, K. L. (2004). Structural equation modeling in management accounting research: Critical analysis and opportunities. Journal Accounting Literature, 23, 49 – 86.

- Snijders, T. A. B., & Bosker, R. J. ( 1999 ). Multilevel analysis : An introduction to basic and advanced multilevel modeling . London : Sage publications.

- Spearman. C. (1904). General intelligence. Objectively determined and measured. American Journal of psychology, 15,201-293.

- Stapleton, L. M. ( 2006 ). An assessment of practical solutions for structural equation modeling with complex sample data. Structural Equation Modeling , 13, 28 – 58.

- Steiger, J. H. (1990). Some additional thoughts on component , and factor indeterminacy. Multivariate Behavioral Research, 25,41-45.

- Steven, J. P. (2009). Applied multivariate statistics for the social sciences. New York: Routledge.

- Tabachnick, B. G., & Fidell, L. S. ( 2007 ). Using multivariate statistics (4 th.ed). Boston: Allyn & Bacon.

- Tanaka, J. S. (1987). “How big is big enough?”: Sample size and goodness of fit in structural equation modeling. Child Development, 58, 134-146.

- Thompson, B. (1988). Program FACSTRAP: A Program that computes bootstrap estimates of factor structure. Educational and Psychological Measurement, 48, 681-686.

- Thompson, B. (2004). Exploratory and confirmatory factor analysis: Understanding concepts and applications. Washington: American psychological Association.

- Tomas, J. M., & Olives, A. ( 1999). Rosenberg's self esteem scale: Two factors or method effects. Structural Equation Modeling, 6, 84 – 98.

- Vassend, O. & Skrondal, A. (1997). Validation of The NEO personality inventory and the five Factor Model: Can findings from exploratory and Confirmatory factor analysis reconciled?. European Journal of Personality, 11, 147 – 166.

- Velicr,W. F., & Jackson, D. N. (1990). Component analysis versus common factor analysis: Some further observations. Multivariate Behavioral Research. 25, 97-114.

- Wherry, R. J. (1931). A new formula of predicting the shrinkage of the coefficient of multiple correlation coefficient. Annual of mathematical statistics, 2, 440-451.

- Widman, K. F. (1990). Bias in pattern loadings represented by common factor analysis and component analysis. Multivariate Behavioral Research, 25, 89-95.

- Wothke, W. (1993). Nonpositive definite matrices in structural equation modeling. In K. A. Bollen & J.S. Long(Eds.), Testing structural equation models(pp.256-293). Newbury park, CA:Sage.

- WU. C. J. ( 2009 ). Factor analysis of the general self – efficacy scale and its relationship with Individualism / collectivism among twenty – five countries: Application of multilevel confirmatory factor analysis. Personality and Individual Differences , 46, 699 – 703.

- Yin, P., & Fan, X. (2001). Estimating R shrinkage in Multiple Regression. Journal of Experimental Education, 69, 203-234.

- Zwick, W. R., &Velicer,W. F. (1986). Comparison of five rules for determining the number of components to retain. Psychological Bulletin, 99, 432-442.