Araştırma Makalesi
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İzleyicinin Medya ve Din Algısı Ölçeği’nin Yapı Geçerliliği

Yıl 2020, Cilt: 3 Sayı: 1, 61 - 77, 29.06.2020

Öz

İstanbul Üniversitesi İletişim Fakültesi’nde yapılmış olan doktora tezinin (Al, 2019) bir parçası olan bu
çalışma, İzleyicinin Medya ve Din Algısı Ölçeği’ni (İMDAÖ) tanıtmayı ve bu ölçeği farklı, bağımsız bir
örneklem üzerinde uygulayarak onun uyum düzeyini doğrulayıcı faktör analizi (DFA) yoluyla ölçmeyi
amaçlamaktadır. Ölçeğin iyi bir model uyumu gösterip göstermediğini tespit etmek için 18 ile 27 yaş
arasında değişen 150 katılımcıdan veri toplanmıştır. Yapılan DFA’da CMIN/DF, RMSEA, CFI, TLI, SRMR,
PNFI ve PCFI uyum indekslerinden faydalanılmıştır. Elde edilen uyum indeksleri, CMIN/DF değerinin
3’ün altında, RMSEA değerinin .06’nın altında, SRMR değerlerinin .08’in altında, CFI ve TLI değerlerinin .95’in üzerinde ve son olarak PNFI ve PCFI değerlerinin .5’in üzerinde olduğunu göstermiştir. Bu
sonuçlar da altı boyuttan –‘Medya Vaizleri ve Temsil’, ‘Siyaset ve Din’, ‘Sekülerleşme / Dine Yabancılaşma’, ‘Dini Yayın Algısı’, ‘Muhalif Kodaçımlama’ ve ‘Dini Medya Okuryazarlığı’– oluşan Medya ve Din Algısı Ölçeği’nin iyi bir model uyumuna sahip olduğunu, yani ölçüm modelinin iyi tanımlanmış olduğunu
ortaya koymuştur.

Kaynakça

  • Al, A. (2019). Medyadaki dini içerikli yayınlarla ilgili izleyici algısı araştırması. İstanbul Üniversitesi Sosyal Bilimler Enstitüsü, Yayımlanmamış Doktora Tezi.
  • Bentler, P. M., and Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, 588-606.
  • Büyüköztürk, Ş. (2004). Sosyal bilimler için veri analizi el kitabı (4. bs.), Ankara, Pegem A Yayıncılık.
  • Byrne, B. M. (2010). Structural equation modeling with AMOS-Basic concepts, applications and programming (2nd ed.), New York: Taylor and Francis Group, LLC.
  • Crowley, S. L., and Fan, X. (1997). Structural equation modeling: Basic concepts and applications in personality assessment research, Journal of Personality Assessment, 68(3), 508-31.
  • Das, S., and Sahu, M. K. (2018). Measuring and validating the scale of entrepreneurial orientation: A confirmatory factor analysis approach, Journal of Entrepreneurship and Management, 7(3), 42-47.
  • Dawson, J. (2017). Analysing quantitative survey data for business and management students, Los Angeles: Sage.
  • Durmuş B., Yurtkoru, E. S., Çinko M. (2011). Sosyal bilimlerde SPSS’le veri analizi (4. bs.), İstanbul: Beta Yayınları.
  • Ferguson, E., and Cox, T. (1993). Exploratory factor analysis: A users’ guide. International Journal of Selection and Assessment, 1, 84-94.
  • Gorsuch, R. L. (1983). Factor analysis (2nd ed.), Hillsdale, NJ: Lawrence Erlbaum.
  • Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.), New Jersey: Pearson Educational Inc.
  • Hatcher, L. (1994). A step-by-step approach to using the SAS system for factor analysis and structural equation modeling, Cary, NC: SAS Institute Inc.
  • Hooper, D., Coughlan, J., Mullen, M. R. (2008). Structural equation modelling: Guidelines for determining model fit. The Electronic Journal of Business Research Methods, 6(1), 53-60.
  • Hu, L. T., and 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. DOI:10.1080/10705519909540118
  • Joormann, J., and Stöber, J. (1997). Measuring facets of worry: A LISREL analysis of the Worry Domains questionnaire. Personality and Individual Differences, 23(5), 827-837.
  • Jöreskog, K. G. and Sörbom, D. (1993). LISREL 8: Structural equation modeling with the SIMPLIS command language, Chicago: Scientific Software International.
  • Kaiser, H. F. (1974). An index of factorial simplicity, Psychometrika, 39, 31-36.
  • Kieffer, K. M. (1999). An introductory primer on the appropriate use of exploratory and confirmatory factor analysis. Research in the Schools, 6, 75-92.
  • Lance, C. E., Butts, M. M., Michels, L. C. (2006). The sources of four commonly reported cutoff criteria: What did they really say? Organizational Research Methods, 9(2), 202-220.
  • Marsh, H. W., Hau, K. T., 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(3), 320-341.
  • MacCallum, R. C., Browne, M. W., Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1, 130-149.
  • McDonald, R. P. and Ho, M. H. R. (2002). Principles and practice in reporting statistical equation analyses. Psychological Methods, 7(1), 64-82.
  • Mulaik, S. A., James, L. R., Van Alstine, J., Bennett, N., Lind, S., Stilwell, C. D. (1989). An evaluation of goodness of fit indices for structural equation models. Psychological Bulletin, 105(3), 430-445.
  • Nunnally, J. C. (1978). Psychometric theory (2nd ed.), New York: McGraw-Hill.
  • Özdamar, K. (1999). Paket programlar ile istatistiksel veri analizi 1, Eskişehir: Kaan Kitabevi.
  • Tabachnick, B. G., and Fidell, L. S. (2007). Using multivariate statistics (5th ed.), New York: Allyn and Bacon.
  • Tavşancıl, E. (2005). Tutumların ölçülmesi ve SPSS ile veri analizi (2. bs.), Ankara: Nobel Yayın Dağıtım.
  • Uzgören, N. (2012). Bilimsel araştırmalarda kullanılan temel istatiksel yöntemler ve SPSS uygulamaları, Bursa: Ekin Yayınevi.
  • Zhang, M. Y., Lee, K. H., Chen, S. C. (2012). Subscriber behaviour in adopting 3G value-added services. African Journal of Business Management, 6(3), 1089-1094.

The Construct Validity of the Scale of Audience Perceptions of Media and Religion

Yıl 2020, Cilt: 3 Sayı: 1, 61 - 77, 29.06.2020

Öz

This study is part of a doctoral dissertation (Al, 2019) at the Faculty of Communication, Istanbul University, Turkey, and it intends to introduce the Scale of Audience Perceptions of Media and Religion
(SAPMR) and to measure its goodness-of-fit with a separate independent sample by deploying a confirmatory factor analysis (CFA). Data were collected from 150 participants, who ranged in age from 18
to 27 years, to measure whether the scale shows a good model fit. In the CFA, CMIN/DF, RMSEA, CFI,
TLI, SRMR, PNFI, and PCFI fit indices were used. The fit indices obtained in the present study showed
that CMIN/DF value was below 3, RMSEA value was below .06, SRMR values were below .08, CFI and
TLI values were above .95, and finally PNFI and PCFI values are above .5. These results revealed that
the SAPMR with six constructs –‘Media Ministers and Representation’, ‘Politics and Religion’, ‘Secularisation / Alienation from Religion’, ‘Perception of Religious Productions’, ‘Decoding in Opposition’,
and ‘Religious Media Literacy’– had a good model fit; namely, its measurement model is well specified.

Kaynakça

  • Al, A. (2019). Medyadaki dini içerikli yayınlarla ilgili izleyici algısı araştırması. İstanbul Üniversitesi Sosyal Bilimler Enstitüsü, Yayımlanmamış Doktora Tezi.
  • Bentler, P. M., and Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, 588-606.
  • Büyüköztürk, Ş. (2004). Sosyal bilimler için veri analizi el kitabı (4. bs.), Ankara, Pegem A Yayıncılık.
  • Byrne, B. M. (2010). Structural equation modeling with AMOS-Basic concepts, applications and programming (2nd ed.), New York: Taylor and Francis Group, LLC.
  • Crowley, S. L., and Fan, X. (1997). Structural equation modeling: Basic concepts and applications in personality assessment research, Journal of Personality Assessment, 68(3), 508-31.
  • Das, S., and Sahu, M. K. (2018). Measuring and validating the scale of entrepreneurial orientation: A confirmatory factor analysis approach, Journal of Entrepreneurship and Management, 7(3), 42-47.
  • Dawson, J. (2017). Analysing quantitative survey data for business and management students, Los Angeles: Sage.
  • Durmuş B., Yurtkoru, E. S., Çinko M. (2011). Sosyal bilimlerde SPSS’le veri analizi (4. bs.), İstanbul: Beta Yayınları.
  • Ferguson, E., and Cox, T. (1993). Exploratory factor analysis: A users’ guide. International Journal of Selection and Assessment, 1, 84-94.
  • Gorsuch, R. L. (1983). Factor analysis (2nd ed.), Hillsdale, NJ: Lawrence Erlbaum.
  • Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.), New Jersey: Pearson Educational Inc.
  • Hatcher, L. (1994). A step-by-step approach to using the SAS system for factor analysis and structural equation modeling, Cary, NC: SAS Institute Inc.
  • Hooper, D., Coughlan, J., Mullen, M. R. (2008). Structural equation modelling: Guidelines for determining model fit. The Electronic Journal of Business Research Methods, 6(1), 53-60.
  • Hu, L. T., and 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. DOI:10.1080/10705519909540118
  • Joormann, J., and Stöber, J. (1997). Measuring facets of worry: A LISREL analysis of the Worry Domains questionnaire. Personality and Individual Differences, 23(5), 827-837.
  • Jöreskog, K. G. and Sörbom, D. (1993). LISREL 8: Structural equation modeling with the SIMPLIS command language, Chicago: Scientific Software International.
  • Kaiser, H. F. (1974). An index of factorial simplicity, Psychometrika, 39, 31-36.
  • Kieffer, K. M. (1999). An introductory primer on the appropriate use of exploratory and confirmatory factor analysis. Research in the Schools, 6, 75-92.
  • Lance, C. E., Butts, M. M., Michels, L. C. (2006). The sources of four commonly reported cutoff criteria: What did they really say? Organizational Research Methods, 9(2), 202-220.
  • Marsh, H. W., Hau, K. T., 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(3), 320-341.
  • MacCallum, R. C., Browne, M. W., Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1, 130-149.
  • McDonald, R. P. and Ho, M. H. R. (2002). Principles and practice in reporting statistical equation analyses. Psychological Methods, 7(1), 64-82.
  • Mulaik, S. A., James, L. R., Van Alstine, J., Bennett, N., Lind, S., Stilwell, C. D. (1989). An evaluation of goodness of fit indices for structural equation models. Psychological Bulletin, 105(3), 430-445.
  • Nunnally, J. C. (1978). Psychometric theory (2nd ed.), New York: McGraw-Hill.
  • Özdamar, K. (1999). Paket programlar ile istatistiksel veri analizi 1, Eskişehir: Kaan Kitabevi.
  • Tabachnick, B. G., and Fidell, L. S. (2007). Using multivariate statistics (5th ed.), New York: Allyn and Bacon.
  • Tavşancıl, E. (2005). Tutumların ölçülmesi ve SPSS ile veri analizi (2. bs.), Ankara: Nobel Yayın Dağıtım.
  • Uzgören, N. (2012). Bilimsel araştırmalarda kullanılan temel istatiksel yöntemler ve SPSS uygulamaları, Bursa: Ekin Yayınevi.
  • Zhang, M. Y., Lee, K. H., Chen, S. C. (2012). Subscriber behaviour in adopting 3G value-added services. African Journal of Business Management, 6(3), 1089-1094.
Toplam 29 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İletişim ve Medya Çalışmaları
Bölüm Araştırma Makaleleri
Yazarlar

Adem Al 0000-0001-5119-1036

Yayımlanma Tarihi 29 Haziran 2020
Yayımlandığı Sayı Yıl 2020 Cilt: 3 Sayı: 1

Kaynak Göster

APA Al, A. (2020). The Construct Validity of the Scale of Audience Perceptions of Media and Religion. Journal of Media and Religion Studies, 3(1), 61-77.

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