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Scale Development in Behavioral Sciences (Based on Exploratory Factor Analysis)

Yıl 2017, , 108 - 126, 20.06.2017
https://doi.org/10.21763/tjfmpc.317880

Öz

In the measurement of a trait in behavioral sciences two basic approaches
stand out: Those are psychometric and impressionistic approaches. Psychometric
approach places emphasis on development of measurement instruments based on
scientific methods with high validity and reliability and is guiding at the
same time. In this study, scale development process in behavioral sciences,
problems encountered, steps to be taken and statistical methods to be used are
discussed in detail and exploratory factor analysis (EFA) as a technique used
in search of dimensions of a scale is mentioned. This study is anticipated to
guide the researchers in scale development process.



Davranış
bilimlerinde, herhangi bir özelliğin ölçülmesi söz konusu olduğunda iki temel yaklaşım
öne çıkmaktadır. Bu yaklaşımlar, psikometrik ve izlenimci yaklaşımdır.
Psikometrik yaklaşım, bilimsel yöntemlere dayanarak geçerliği ve güvenirliği
yüksek ölçme araçlarının geliştirilmesine önem verir, aynı zamanda yol
gösterir. Bu makalede, davranış bilimlerinde ölçek geliştirme süreci,
karşılaşılabilecek sorunlar, izlenmesi gereken adımlar ve kullanılabilecek
istatistiksel yöntemler ayrıntılı olarak ele alınmış, ölçek boyutlarını
keşfetmek amacıyla başvurulan açıklayıcı faktör analizi (AFA) tekniğine yer
verilmiştir. Makalenin, ölçek geliştirmek isteyen araştırmacılara yol
göstereceği umulmaktadır.



 

Kaynakça

  • 1. Cronbach, L. J. Essentials of psychological testing. New York: Harper Collins Publishers; 1960; 105-126.
  • 2. Özgüven, İ. E. Psikolojik testler. Ankara: Pdrem Yayınları. 2011; 46-52.
  • 3. Anastasi, A. Psychological testing. New York: Macmillan Publishing Co., Inc. 1982; 34.
  • 4. McReynolds, P. The motivational psychology of Jeremy Bentham: I. Background and general approach. J. Hist. Behav. Sci., 1968; 4: 230–244.
  • 5. Crocker, L. ve Algina, J. Introduction to classical and modern test theory. New York: Holt, Rinehart and Winston, Inc. 1986; 66-84.
  • 6. Murphy K.R. ve Davidshofer C.O. Psychological testing: principles and applications. New Jersey: Pearson Education International; 2005; 30-260.
  • 7. Furr M.R. ve Bacharach V.R. Psychometrics: an introduction. California: Sage Publications; 2008; 24-180.
  • 8. Cohen R.J. ve Swerdlik M.E. Psychological testing and assessment. Boston: McGraw-Hill Companies; 2010; 120- 190.
  • 9. Tavşancıl, E. Tutumların ölçülmesi ve SPSS ile veri analizi. Ankara: Nobel Yayıncılık; 2010; 34-85.
  • 10. Edenborough R. Using psychometrics: a practical guide to testing and assessment. London: Kogan Page; 1999; 54-55.
  • 11. Erkuş, A. Psikolojide ölçme ve ölçek geliştirme-1: Temel kavramlar ve işlemler. Ankara: Pegem Akademi; 2012a; 25-112.
  • 12. Şahin, N. Psikoloji araştırmalarında ölçek kullanımı. Türk Psikoloji Dergisi, 1994; 9(33), 19-26.
  • 13. Hambleton, R.K. ve Patsula, L. Increasing the validity of adapted tests: Myths to be avoided and guidelines for improving test adaptation practices. Journal of Applied Testing Technology, 1999; 1(1), 1-30.
  • 14. Çüm, S. ve Koç, N. Türkiye’de psikoloji ve eğitim bilimleri dergilerinde yayımlanan ölçek geliştirme ve uyarlama çalışmalarının incelenmesi. Eğitim Bilimleri ve Uygulama, 2013; 12(24), 115-135.
  • 15. Turgut, F. Test geliştirme teknikleri: Ders notları. Ankara: Hacettepe Üniversitesi Yayınları. 1978. 15-17.
  • 16. Rust J. ve Golombok S. Modern Psychometrics: the science of psychological assessment. New York: Routledge. 1997; 46-81.
  • 17. Tezbaşaran, A. Likert tipi ölçek hazırlama kılavuzu. Ankara: Türk Psikologlar Derneği Yayınları. 2008. 27-48.
  • 18. Coaley K. Psychological assessment and psychometrics. California: Sage Publications. 2010; 255-262.
  • 19. Cordes, C.L. ve Dougherty, T.W. A review and an integration of resarch on job burnout. Academy of Management Review, 1993; 18(4), 621-656.
  • 20. Huberman, A.M. ve Vandenberghe, R. Understanding and Preventing Teacher Burnout. Cambridge: Cambridge University Press. 1999; 62.
  • 21. Brown, T.A. Confirmatory factor analysis for applied research. New York: The Guilford Press. 2015; 19-33.
  • 22. Field, A. Discovering statistics using SPSS. London: Sage Publications Ltd. 2009; 627-681.
  • 23. Williams, B., Onsman, A. ve Brown, T. Exploratory factor analysis: A five step guide for novices. Journal of Emergency Primary Health Care, 2010; 8(3), 1-13.
  • 24. Tabachnick, B. ve Fidell, L. Using multivariate statistics. New York: Herper Collins College Publishers. 1996; 764-792.
  • 25. Hair, J., Anderson, R.E., Tatham, R.L. ve Black, W.C. Multivariate data analysis. 4th ed. New Jersey: Prentice-Hall Inc. 1995; 42-78.
  • 26. Comrey, A.L. ve Lee, H.B. A first course in factor analysis. Hillsdale, NJ: Erlbaum. 1992; 22-24.
  • 27. Gorsuch, R. L. Factor analysis (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum. 1983; 33-40.
  • 28. Hatcher, L. A step-by-step approach to using the SAS. Cary, NC: SAS Institute, Inc. 1994; 210.
  • 29. Bryant, F.B. ve Yarnold, P.R. Principal components analysis and exploratory and confirmatory factor analysis. Washington, DC: American Psychological Association. 1995; 270.
  • 30. Suhr, D. Exploratory or Confirmatory Factor Analysis. SAS Users Group International Conference 2006; pp. 1 – 17, Cary: SAS Institute, Inc.
  • 31. Everitt, S. Multivariate analysis: The need for data and other problems. British Journal of Psychiatry. 1975;126, 227-240.
  • 32. Nunnally, J.C. Psychometric theory. New york: McGraw-Hill. 1978; 430-520.
  • 33. Velicer, W.F. ve Fava, J.L. Effects of variable and subject sampling on factor pattern recovery. Psychological Methods, 1998 . 3(2), 231-251.
  • 34. Cool, A. L. A review of methods for dealing with missing data (rapor). Annual Meeting of the Southwest Educational Resarch Association. Dallas. 2000.
  • 35. Roth, P. L. Missing data: A conceptual review for applied psychologists. Personnel Psychology, 1994;3(1), 537-560.
  • 36. Alpar, R. Çok değişkenli istatistiksel yöntemler. Ankara: Detay Yayıncılık. 2011; 286-301.
  • 37. Schafer, J. L. Multiple imputation: a primer. Statistical Methods on Medical Resarch, 1999; 8(1), 3-15.
  • 38. Osborne, J. W. Best practices in data cleaning. California: Sage Publication, Inc. 2013; 18-60.
  • 39. Pett, M.A., Lackey, N.R. ve Sullivan, J.J. Making Sense of Factor Analysis: The use of factor analysis for instrument development in health care research. California: Sage Publications. 2003; 23-70.
  • 40. Beavers, A.S., Lounsbury, J.W., Richards, J.K., Huck, S.W., Skolits, G.J. ve Esquivel, .L. Practical considerations for using exploratory factor analysis in educational research. Practical Assessment, Research and Evaluation, 2013; 18(6), 1-13.
  • 41. Byrne, B.M. Structural equation modeling with AMOS: Basic concepts, applications and programming. Mahwah, NJ: Lawrence Erlbaum Associates. 2001; 92-93.
  • 42. Brown, J.D. Principal component analysis and exploratory factor analysis: Definitions, differences and choices. JALT Testing and Evaluation Newsletter, 2009; 13(1), 26-30.
  • 43. Osborne, J.W. ve Costello, A.B. Best practices in exploratory factor analysis: Four recommendations for getting the most from you analysis. Pan-Pacific Management Review, 2009; 12(2), 131-146.
  • 44. Widaman, K.F. Common factor analysis versus principal component analysis: Differential bias in representing model parameters. Multivariate Behavioral Research, 1993; 28(3), 263-311.
  • 45. Snook, S.C. ve Gorsuch, R.L. Component anaylsis versus common factor analysis: A monte carlo study. Psychological Bulletin, 1989; 106, 148-154.
  • 46. Fabrigar, L. R.,Wegener,D. T., MacCallum, R. C., ve Strahan, E. J. Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 1999; 4(3), 272-299.
  • 47. Coughlin, K.B. An analysis of factor extraction strategies: A study of the relative strenghts of principal axis, ordinary least squares and maximum likelihood factor extraction methods in research contexts. Yayımlanmamış doktora tezi, University of South Florida, Tampa, FL. 2013.
  • 48. Horn, J. L. A rationale and test for the number of factors in factor analysis. Psychometrika, 1965; 30(2),179-85.
  • 49. Linn, R. L. A Monte Carlo approach to the number of factors problem. Psychometrika, 1968; 33, 37-71.
  • 50. Silverstein, A. B. Note on the parallel analysis criterion for determining the number of common factors or principal components. Psychological Reports, 1987; 61, 351-354.
  • 51. Eaton, C. A., Velicer, W. F. ve Fava, J. L. Determining the number of components: An evaluation of parallel analysis and the minimum average partial correlation procedures. Unpublished manuscript. 1999.
  • 52. Zwick,W. R. ve Velicer,W. F. Factors influencing five rules for determining the number of components to retain. Psychological Bulletin, 1986; 99, 432-442
  • 53. Hayton, J.C., Allen, D.G. ve Scarpello, V. Factor retention decision in exploratoy factor analysis: A tutorial on parallel analysis. Organizational Research Methods, 2004; 7(2), 191-205.
  • 54. Thompson, B. Exploratory and confirmatory factor analysis: understanding concepts and applications. Washington, DC: American Psychological Association. 2004; 44-47.
  • 55. Henson, R.K. ve Roberts, J.K. Use of exploratory factor analysis in published research: common errors and some comment on improved practice. Educational and Psychological Measurement, 2006; 66, 393-416.
  • 56. Kim, J.O. ve Mueller, C.W. Introduction to factor analysis: What it is and how do it. Beverly Hills, CA: Sage Publications. 1978; 54.
  • 57. Yurdabakan, İ. Egitimde Kullanılan Olçme Araclarının Nitelikleri. In S. Erkan & M. Gomleksiz (Eds.), Egitimde olcme ve degerlendirme. Ankara: Nobel Yayın Dagıtım. 2008; 38-66.
  • 58. Turgut, F. ve Baykul, Y. Eğitimde ölçme ve değerlendirme. Ankara: Pegem Akademi Yayıncılık. 2012; 76-89.
  • 59. Yang, Y. ve Green, S.B. Coefficient alpha a reliability coefficient for the 21st century? Journal of Psychoeducational Assessment. 2011; 29(4), 377-392.
  • 60. Schmitt, N. Uses and abuses of coefficient alpha. Psychological Assessment, 1996; 8, 350-353.
  • 61. Osburn, H. G. Coefficient alpha and related internal consistency reliability coefficients. Psychological Methods, 2000; 5, 343-355.
  • 62. Cronbach, L. J. My current thoughts on coefficient alpha and successor procedures. Educational and Psychological Measurement, 2004; 64, 391-418.
  • 63. Tan, Ş. Misuses of KR-20 and Cronbach’s Alpha Reliability Coefficients. Education and Science, 2009; 34(152), 101-112.
  • 64. Erkuş, A. Psikometri üzerine yazılar. Ankara: Türk Psikologlar Derneği Yayınları. 2003; 69.
  • 65. Tavakol, M. ve Dennick, R. Making sense of cronbach’s alpha. International Journal of Medical Education, 2011; 2, 53-55.
  • 66. Widhiarso, W. ve Ravand, H. Estimating reliability coefficient for multidimensional measures: A pedagogical illustration. Review of Psychology, 2014; 2, 111-121.
  • 67. Cronbach, L. J., Schonemann, P. ve McKie, D. Alpha coefficients for stratified-paralel tests. Educational and Psychological Measurement, 1965; 25, 291-312.
  • 68. Moiser, C. On the reliability of a weighted composite. Psychometrica, 1943; 8(3), 161-168.
  • 69. Wang, M.V. ve Stanley, J.C. Differential weighting: A review of methods and empirical studies. Review of Educational Research, 1970; 40, 663-705.
  • 70. Novick, M.R. ve Lewis, C. Coefficient alpha: A basic introduction from the perpectives of classical test theory and structural equation modeling. Structural Equation Modeling, 1967; 2, 255-273.
  • 71. Yurdugül, H. The comparison of reliability coefficients in parallel, tau-equivalent and congeneric measurements. Journal of Educational Sciences, 2006; 39(1), 15-37.
  • 72. Raykov, T. ve Shrout, P.E. Reliability of scales with general structure: Point and interval estimation using a structural equation modeling approach. Structural Equation Modeling, 2002; 9(2), 195-212.
  • 73. Amerikan Eğitim Araştırmaları Birliği, Amerikan Psikoloji Birliği, Eğitim Ölçümleri Uluslar arası Konseyi. Eğitimde ve psikolojide ölçme standartları (S. Hovardaoğlu ve N. Sezgin, Çeviri). Ankara: Türk Psikologlar Derneği ve ÖSYM yayını. 1997; 62-70.
  • 74. Yurdugül, H. ve Alsancak Sırakaya, D. Çevrimiçi öğrenme hazır bulunuşluluk ölçeği: Geçerlik ve güvenirlik çalışması. Eğitim ve Bilim, 2013;169(38), 391-406.
Yıl 2017, , 108 - 126, 20.06.2017
https://doi.org/10.21763/tjfmpc.317880

Öz

Kaynakça

  • 1. Cronbach, L. J. Essentials of psychological testing. New York: Harper Collins Publishers; 1960; 105-126.
  • 2. Özgüven, İ. E. Psikolojik testler. Ankara: Pdrem Yayınları. 2011; 46-52.
  • 3. Anastasi, A. Psychological testing. New York: Macmillan Publishing Co., Inc. 1982; 34.
  • 4. McReynolds, P. The motivational psychology of Jeremy Bentham: I. Background and general approach. J. Hist. Behav. Sci., 1968; 4: 230–244.
  • 5. Crocker, L. ve Algina, J. Introduction to classical and modern test theory. New York: Holt, Rinehart and Winston, Inc. 1986; 66-84.
  • 6. Murphy K.R. ve Davidshofer C.O. Psychological testing: principles and applications. New Jersey: Pearson Education International; 2005; 30-260.
  • 7. Furr M.R. ve Bacharach V.R. Psychometrics: an introduction. California: Sage Publications; 2008; 24-180.
  • 8. Cohen R.J. ve Swerdlik M.E. Psychological testing and assessment. Boston: McGraw-Hill Companies; 2010; 120- 190.
  • 9. Tavşancıl, E. Tutumların ölçülmesi ve SPSS ile veri analizi. Ankara: Nobel Yayıncılık; 2010; 34-85.
  • 10. Edenborough R. Using psychometrics: a practical guide to testing and assessment. London: Kogan Page; 1999; 54-55.
  • 11. Erkuş, A. Psikolojide ölçme ve ölçek geliştirme-1: Temel kavramlar ve işlemler. Ankara: Pegem Akademi; 2012a; 25-112.
  • 12. Şahin, N. Psikoloji araştırmalarında ölçek kullanımı. Türk Psikoloji Dergisi, 1994; 9(33), 19-26.
  • 13. Hambleton, R.K. ve Patsula, L. Increasing the validity of adapted tests: Myths to be avoided and guidelines for improving test adaptation practices. Journal of Applied Testing Technology, 1999; 1(1), 1-30.
  • 14. Çüm, S. ve Koç, N. Türkiye’de psikoloji ve eğitim bilimleri dergilerinde yayımlanan ölçek geliştirme ve uyarlama çalışmalarının incelenmesi. Eğitim Bilimleri ve Uygulama, 2013; 12(24), 115-135.
  • 15. Turgut, F. Test geliştirme teknikleri: Ders notları. Ankara: Hacettepe Üniversitesi Yayınları. 1978. 15-17.
  • 16. Rust J. ve Golombok S. Modern Psychometrics: the science of psychological assessment. New York: Routledge. 1997; 46-81.
  • 17. Tezbaşaran, A. Likert tipi ölçek hazırlama kılavuzu. Ankara: Türk Psikologlar Derneği Yayınları. 2008. 27-48.
  • 18. Coaley K. Psychological assessment and psychometrics. California: Sage Publications. 2010; 255-262.
  • 19. Cordes, C.L. ve Dougherty, T.W. A review and an integration of resarch on job burnout. Academy of Management Review, 1993; 18(4), 621-656.
  • 20. Huberman, A.M. ve Vandenberghe, R. Understanding and Preventing Teacher Burnout. Cambridge: Cambridge University Press. 1999; 62.
  • 21. Brown, T.A. Confirmatory factor analysis for applied research. New York: The Guilford Press. 2015; 19-33.
  • 22. Field, A. Discovering statistics using SPSS. London: Sage Publications Ltd. 2009; 627-681.
  • 23. Williams, B., Onsman, A. ve Brown, T. Exploratory factor analysis: A five step guide for novices. Journal of Emergency Primary Health Care, 2010; 8(3), 1-13.
  • 24. Tabachnick, B. ve Fidell, L. Using multivariate statistics. New York: Herper Collins College Publishers. 1996; 764-792.
  • 25. Hair, J., Anderson, R.E., Tatham, R.L. ve Black, W.C. Multivariate data analysis. 4th ed. New Jersey: Prentice-Hall Inc. 1995; 42-78.
  • 26. Comrey, A.L. ve Lee, H.B. A first course in factor analysis. Hillsdale, NJ: Erlbaum. 1992; 22-24.
  • 27. Gorsuch, R. L. Factor analysis (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum. 1983; 33-40.
  • 28. Hatcher, L. A step-by-step approach to using the SAS. Cary, NC: SAS Institute, Inc. 1994; 210.
  • 29. Bryant, F.B. ve Yarnold, P.R. Principal components analysis and exploratory and confirmatory factor analysis. Washington, DC: American Psychological Association. 1995; 270.
  • 30. Suhr, D. Exploratory or Confirmatory Factor Analysis. SAS Users Group International Conference 2006; pp. 1 – 17, Cary: SAS Institute, Inc.
  • 31. Everitt, S. Multivariate analysis: The need for data and other problems. British Journal of Psychiatry. 1975;126, 227-240.
  • 32. Nunnally, J.C. Psychometric theory. New york: McGraw-Hill. 1978; 430-520.
  • 33. Velicer, W.F. ve Fava, J.L. Effects of variable and subject sampling on factor pattern recovery. Psychological Methods, 1998 . 3(2), 231-251.
  • 34. Cool, A. L. A review of methods for dealing with missing data (rapor). Annual Meeting of the Southwest Educational Resarch Association. Dallas. 2000.
  • 35. Roth, P. L. Missing data: A conceptual review for applied psychologists. Personnel Psychology, 1994;3(1), 537-560.
  • 36. Alpar, R. Çok değişkenli istatistiksel yöntemler. Ankara: Detay Yayıncılık. 2011; 286-301.
  • 37. Schafer, J. L. Multiple imputation: a primer. Statistical Methods on Medical Resarch, 1999; 8(1), 3-15.
  • 38. Osborne, J. W. Best practices in data cleaning. California: Sage Publication, Inc. 2013; 18-60.
  • 39. Pett, M.A., Lackey, N.R. ve Sullivan, J.J. Making Sense of Factor Analysis: The use of factor analysis for instrument development in health care research. California: Sage Publications. 2003; 23-70.
  • 40. Beavers, A.S., Lounsbury, J.W., Richards, J.K., Huck, S.W., Skolits, G.J. ve Esquivel, .L. Practical considerations for using exploratory factor analysis in educational research. Practical Assessment, Research and Evaluation, 2013; 18(6), 1-13.
  • 41. Byrne, B.M. Structural equation modeling with AMOS: Basic concepts, applications and programming. Mahwah, NJ: Lawrence Erlbaum Associates. 2001; 92-93.
  • 42. Brown, J.D. Principal component analysis and exploratory factor analysis: Definitions, differences and choices. JALT Testing and Evaluation Newsletter, 2009; 13(1), 26-30.
  • 43. Osborne, J.W. ve Costello, A.B. Best practices in exploratory factor analysis: Four recommendations for getting the most from you analysis. Pan-Pacific Management Review, 2009; 12(2), 131-146.
  • 44. Widaman, K.F. Common factor analysis versus principal component analysis: Differential bias in representing model parameters. Multivariate Behavioral Research, 1993; 28(3), 263-311.
  • 45. Snook, S.C. ve Gorsuch, R.L. Component anaylsis versus common factor analysis: A monte carlo study. Psychological Bulletin, 1989; 106, 148-154.
  • 46. Fabrigar, L. R.,Wegener,D. T., MacCallum, R. C., ve Strahan, E. J. Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 1999; 4(3), 272-299.
  • 47. Coughlin, K.B. An analysis of factor extraction strategies: A study of the relative strenghts of principal axis, ordinary least squares and maximum likelihood factor extraction methods in research contexts. Yayımlanmamış doktora tezi, University of South Florida, Tampa, FL. 2013.
  • 48. Horn, J. L. A rationale and test for the number of factors in factor analysis. Psychometrika, 1965; 30(2),179-85.
  • 49. Linn, R. L. A Monte Carlo approach to the number of factors problem. Psychometrika, 1968; 33, 37-71.
  • 50. Silverstein, A. B. Note on the parallel analysis criterion for determining the number of common factors or principal components. Psychological Reports, 1987; 61, 351-354.
  • 51. Eaton, C. A., Velicer, W. F. ve Fava, J. L. Determining the number of components: An evaluation of parallel analysis and the minimum average partial correlation procedures. Unpublished manuscript. 1999.
  • 52. Zwick,W. R. ve Velicer,W. F. Factors influencing five rules for determining the number of components to retain. Psychological Bulletin, 1986; 99, 432-442
  • 53. Hayton, J.C., Allen, D.G. ve Scarpello, V. Factor retention decision in exploratoy factor analysis: A tutorial on parallel analysis. Organizational Research Methods, 2004; 7(2), 191-205.
  • 54. Thompson, B. Exploratory and confirmatory factor analysis: understanding concepts and applications. Washington, DC: American Psychological Association. 2004; 44-47.
  • 55. Henson, R.K. ve Roberts, J.K. Use of exploratory factor analysis in published research: common errors and some comment on improved practice. Educational and Psychological Measurement, 2006; 66, 393-416.
  • 56. Kim, J.O. ve Mueller, C.W. Introduction to factor analysis: What it is and how do it. Beverly Hills, CA: Sage Publications. 1978; 54.
  • 57. Yurdabakan, İ. Egitimde Kullanılan Olçme Araclarının Nitelikleri. In S. Erkan & M. Gomleksiz (Eds.), Egitimde olcme ve degerlendirme. Ankara: Nobel Yayın Dagıtım. 2008; 38-66.
  • 58. Turgut, F. ve Baykul, Y. Eğitimde ölçme ve değerlendirme. Ankara: Pegem Akademi Yayıncılık. 2012; 76-89.
  • 59. Yang, Y. ve Green, S.B. Coefficient alpha a reliability coefficient for the 21st century? Journal of Psychoeducational Assessment. 2011; 29(4), 377-392.
  • 60. Schmitt, N. Uses and abuses of coefficient alpha. Psychological Assessment, 1996; 8, 350-353.
  • 61. Osburn, H. G. Coefficient alpha and related internal consistency reliability coefficients. Psychological Methods, 2000; 5, 343-355.
  • 62. Cronbach, L. J. My current thoughts on coefficient alpha and successor procedures. Educational and Psychological Measurement, 2004; 64, 391-418.
  • 63. Tan, Ş. Misuses of KR-20 and Cronbach’s Alpha Reliability Coefficients. Education and Science, 2009; 34(152), 101-112.
  • 64. Erkuş, A. Psikometri üzerine yazılar. Ankara: Türk Psikologlar Derneği Yayınları. 2003; 69.
  • 65. Tavakol, M. ve Dennick, R. Making sense of cronbach’s alpha. International Journal of Medical Education, 2011; 2, 53-55.
  • 66. Widhiarso, W. ve Ravand, H. Estimating reliability coefficient for multidimensional measures: A pedagogical illustration. Review of Psychology, 2014; 2, 111-121.
  • 67. Cronbach, L. J., Schonemann, P. ve McKie, D. Alpha coefficients for stratified-paralel tests. Educational and Psychological Measurement, 1965; 25, 291-312.
  • 68. Moiser, C. On the reliability of a weighted composite. Psychometrica, 1943; 8(3), 161-168.
  • 69. Wang, M.V. ve Stanley, J.C. Differential weighting: A review of methods and empirical studies. Review of Educational Research, 1970; 40, 663-705.
  • 70. Novick, M.R. ve Lewis, C. Coefficient alpha: A basic introduction from the perpectives of classical test theory and structural equation modeling. Structural Equation Modeling, 1967; 2, 255-273.
  • 71. Yurdugül, H. The comparison of reliability coefficients in parallel, tau-equivalent and congeneric measurements. Journal of Educational Sciences, 2006; 39(1), 15-37.
  • 72. Raykov, T. ve Shrout, P.E. Reliability of scales with general structure: Point and interval estimation using a structural equation modeling approach. Structural Equation Modeling, 2002; 9(2), 195-212.
  • 73. Amerikan Eğitim Araştırmaları Birliği, Amerikan Psikoloji Birliği, Eğitim Ölçümleri Uluslar arası Konseyi. Eğitimde ve psikolojide ölçme standartları (S. Hovardaoğlu ve N. Sezgin, Çeviri). Ankara: Türk Psikologlar Derneği ve ÖSYM yayını. 1997; 62-70.
  • 74. Yurdugül, H. ve Alsancak Sırakaya, D. Çevrimiçi öğrenme hazır bulunuşluluk ölçeği: Geçerlik ve güvenirlik çalışması. Eğitim ve Bilim, 2013;169(38), 391-406.
Toplam 74 adet kaynakça vardır.

Ayrıntılar

Bölüm Derleme
Yazarlar

İrfan Yurdabakan

Sait Çüm

Yayımlanma Tarihi 20 Haziran 2017
Gönderilme Tarihi 31 Mayıs 2017
Yayımlandığı Sayı Yıl 2017

Kaynak Göster

Vancouver Yurdabakan İ, Çüm S. Scale Development in Behavioral Sciences (Based on Exploratory Factor Analysis). TJFMPC. 2017;11(2):108-26.

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