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Davranışsal İletişim Araştırmalarında Aracılık Testine Genel Bir Bakış

Year 2022, , 392 - 410, 26.12.2022
https://doi.org/10.52642/susbed.1158738

Abstract

Davranışsal iletişim araştırmacıları, son dönemlerde değişkenler arasındaki ilişkilerin ‘neden’ ve ‘nasıl’ gerçekleştiğine dair açıklamalar sunmak amacıyla aracılık testine başvurmaktadırlar. Bu ilişkilerin ardında yatan mekanizmanın açıklanmasına imkân sunan aracılık testinin araştırmacılar tarafından kullanılması araştırma modelinin hikayesini okuyucuya aktarabilmek için kaçınılmazdır. Ancak yakın geçmişte aracılık testinin uygulanmasına yönelik metodolojik tartışmaların işaret ettiği üzere aracılık testinin felsefik arka planının yeterince anlaşılmadığı ve bu doğrultuda metodolojik düzeyde ezber uygulamaların davranışsal iletişim araştırmalarında özellikle sergilendiği dikkat çekmektedir. Bu sorunsalın önüne geçebilmek amacıyla gerçekleştirilen bu metodolojik çalışmada, aracılık testinin felsefik ve metodolojik arka planı tartışılmaya ve genel bir bakış sunulmaya çalışılmaktadır. Ayrıca, ilgili tartışmanın yeni bir metodolojik bilgi birikimi oluşturmasının yanında, mevcut durumun daha anlaşılır kılınarak sade bir şekilde araştırmacılara sunulması da bu çalışmada amaçlanmaktadır. Gelecekte davranışsal iletişim araştırmacıları aracı değişkenli modellerinin test ederken açık prosedür yaklaşımını kullanması (önyükleme gibi), dolaylı etki için bir sınıflandırma yapmaması, aracılık için hipotezlerini literatür veya teorilere göre geliştirerek bölümleme veya iletimsel yaklaşımı tercih etmesi beklenmektedir.

References

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Year 2022, , 392 - 410, 26.12.2022
https://doi.org/10.52642/susbed.1158738

Abstract

References

  • Abeza, G., & Sanderson, J. (2022). Theory and social media in sport studies. International Journal of Sport Communication, 28(6), 1–9. https://doi.org/10.1123/ijsc.2022-0108).
  • Aguinis, H., Edwards, J. R., & Bradley, K. J. (2017). Improving our understanding of moderation and mediation in strategic management research. Organizational Research Methods, 20(4), 665-685. https://doi.org/10.1177/1094428115627498
  • Alfons, A., Ateş, N. Y., & Groenen, P. J. F. (2022). A robust bootstrap test for mediation analysis. Organizational Research Methods, 25(3), 591-617. https://doi.org/10.1177/1094428121999096
  • Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182. https://doi.org/10.1037/0022-3514.51.6.1173
  • Bozkurt, S. (2021). Pazarlama alanında en sık kullanılan Process makro modellerinin veri setleriyle incelenmesi. Ekin Yayınevi.
  • Bullock, H. E., Harlow, L. L., & Mulaik, S. A. (1994). Causation issues in structural equation modeling research. Structural Equation Modeling: A Multidisciplinary Journal, 1(3), 253-267. https://doi.org/10.1080/10705519409539977
  • Burt, I., & Hampton, C. (2017). Moderation and mediation in behavioural accounting research. İçinde T. Libby & L. Thorne (Ed.), The routledge companion to behavioural accounting research (ss. 373-387). Routledge. https://doi.org/10.4324/9781315710129-24
  • Chan, M., Hu, P., & K. F. Mak, M. (2022). Mediation analysis and warranted inferences in media and communication research: Examining research design in communication journals from 1996 to 2017. Journalism & Mass Communication Quarterly, 99(2), 463-486. https://doi.org/10.1177/1077699020961519
  • DiCiccio, T. J., & Efron, B. (1996). Bootstrap confidence intervals. Statistical Science, 11(3). https://doi.org/10.1214/ss/1032280214
  • Dolma, S. (2021, 9 Ocak). Online eğitim “nicel veri analizlerinde aracı değişken mediator kavramı ve aracı değişkenli modeller” [Video]. YouTube. https://www.youtube.com/watch?v=_NsOYFJy4wU&t=3847s&ab_channel=NecmettinErbakan%C3%9Cniversitesi
  • Fang, J., Wang, X., Wen, Z., & Zhou, J. (2020). Fear of missing out and problematic social media use as mediators between emotional support from social media and phubbing behavior. Addictive Behaviors, 107, 106430. https://doi.org/10.1016/j.addbeh.2020.106430
  • Fritz, M. S., & MacKinnon, D. P. (2007). Required sample size to detect the mediated effect. Psychological Science, 18(3), 233-239. https://doi.org/10.1111/j.1467-9280.2007.01882.x
  • Fritz, M. S., Taylor, A. B., & MacKinnon, D. P. (2012). Explanation of two anomalous results in statistical mediation analysis. Multivariate Behavioral Research, 47(1), 61-87. https://doi.org/10.1080/00273171.2012.640596
  • Guide, V. D. R., & Ketokivi, M. (2015). Notes from the Editors: Redefining some methodological criteria for the journal. Journal of Operations Management, 37(1), v-viii. https://doi.org/10.1016/S0272-6963(15)00056-X
  • Gürbüz, S. (2019). Sosyal bilimlerde aracı, düzenleyici ve durumsal etki analizleri. Seçkin Yayıncılık.
  • Gürbüz, S., & Bayık, M. E. (2021). Aracılık modellerinin analizinde yeni yaklaşım: Baron ve Kenny’nin yöntemi hâlâ geçerli mi? Türk Psikoloji Dergisi, 37(99), 1-14. https://doi.org/10.31828/tpd1300443320191125m000031
  • Hair, J. F., Black, C. W., Babin, J. B., & Anderson, E. R. (2019). Multivariate data analysis (8th edition). Cengage.
  • Hair, J. F., Hult, G. T., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd Edition). SAGE Publications.
  • Hayes, A. F. (2009). Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Communication Monographs, 76(4), 408-420. https://doi.org/10.1080/03637750903310360
  • Hayes, A. F. (2018). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (2nd Edition). The Guilford Press.
  • Hayes, A. F., & Preacher, K. J. (2013). Conditional process modeling: Using structural equation modeling to examine contingent causal processes. İçinde Structural equation modeling: A second course (2nd Edition, ss. 219-266). IAP Information Age Publishing.
  • Hayes, A. F., & Rockwood, N. J. (2017). Regression-Based Statistical Mediation and Moderation Analysis in Clinical Research: Observations, Recommendations, and Implementation. Behaviour Research and Therapy, 98, 39-57. https://doi.org/10.1016/j.brat.2016.11.001
  • Holbert, R. L., & Stephenson, M. T. (2003). The importance of indirect effects in media effects research: Testing for mediation in structural equation modeling. Journal of Broadcasting & Electronic Media, 47(4), 556-572. https://doi.org/10.1207/s15506878jobem4704_5
  • Jose, P. E. (2013). Doing statistical mediation and moderation. The Guilford Press.
  • Jose, P. E. (2016). The merits of using longitudinal mediation. Educational Psychologist, 51(3-4), 331-341. https://doi.org/10.1080/00461520.2016.1207175
  • Jose, P. E. (2019). Mediation and moderation. İçinde G. R. Hancock, L. M. Stapleton, & R. O. Mueller (Ed.), The reviewer’s guide to quantitative methods in the social sciences (2nd Edition, ss. 248-259). Routledge. https://doi.org/10.4324/9781315755649
  • Katz, E., & Lazarsfeld, P. F. (1955). Personal influence: The part played by people in the flow of mass communications. Free Press.
  • Kenny, D. A. (2021, Mayıs 4). Mediation. https://davidakenny.net/cm/mediate.htm
  • Kline, R. B. (2015). The mediation myth. Basic and Applied Social Psychology, 37(4), 202-213. https://doi.org/10.1080/01973533.2015.1049349
  • Koschate-Fischer, N., & Schwille, E. (2018). Mediation analysis in experimental research. İçinde C. Homburg, M. Klarmann, & A. Vomberg (Ed.), Handbook of market research (ss. 1-49). Springer International Publishing. https://doi.org/10.1007/978-3-319-05542-8_34-1
  • Koshksaray, A. A., Franklin, D., & Heidarzadeh Hanzaee, K. (2015). The relationship between e-lifestyle and ınternet advertising avoidance. Australasian Marketing Journal, 23(1), 38-48. https://doi.org/10.1016/j.ausmj.2015.01.002
  • LeBreton, J. M., Wu, J., & Bing, M. N. (2009). The truth (s) on testing for mediation in the social and organizational sciences. İçinde E. C. Lance & J. R. Vandenberg (Ed.), Statistical and methodological myths and urban legends: Doctrine, verity and fable in the organizational and social sciences (ss. 107-141). Routledge.
  • MacKinnon, D. (2008). Introduction to statistical mediation analysis. Routledge.
  • MacKinnon, D. P., Lockwood, C. M., Hoffman, J. M., West, S. G., & Sheets, V. (2002). A comparison of methods to test mediation and other intervening variable effects. Psychological Methods, 7(1), 83-104. https://doi.org/10.1037/1082-989X.7.1.83
  • MacKinnon, D. P., Lockwood, C. M., & Williams, J. (2004). Confidence limits for the indirect effect: Distribution of the product and resampling methods. Multivariate Behavioral Research, 39(1), 99-128. https://doi.org/10.1207/s15327906mbr3901_4
  • McLeod, J. M., Kosicki, G. M., & Pan, Z. (1991). On understanding and misunderstanding media effects. İçinde J. Curran & M. Gurevitch (Ed.), Mass media and society (ss. 235-266). Edward Arnold.
  • Memon, M. A., Cheah, J.-H., Ramayah, T., Ting, H., & Chuah, F. (2018). Mediation analysis ıssues and recommendations. Journal of Applied Structural Equation Modeling, 2(1), 1-9.
  • Namazi, M., & Namazi, N.-R. (2016). Conceptual analysis of moderator and mediator variables in business research. Procedia Economics and Finance, 36, 540-554. https://doi.org/10.1016/S2212-5671(16)30064-8
  • Nitzl, C., Roldan, J. L., & Cepeda, G. (2016). Mediation analysis in partial least squares path modeling: Helping researchers discuss more sophisticated models. Industrial Management & Data Systems, 116(9), 1849-1864. https://doi.org/10.1108/IMDS-07-2015-0302
  • Pesämaa, O., Zwikael, O., Hair, J. F., & Huemann, M. (2021). Publishing quantitative papers with rigor and transparency. International Journal of Project Management, 39(3), 217-222. https://doi.org/10.1016/j.ijproman.2021.03.001
  • Pieters, R. (2017). Meaningful mediation analysis: Plausible causal inference and informative communication. Journal of Consumer Research, 44(3), 1-69. https://doi.org/10.1093/jcr/ucx081
  • Preacher, K. J., & Hayes, A. F. (2008a). Contemporary approaches to assessing mediation in communication research. İçinde A. Hayes, M. Slater, & L. Snyder, The sage sourcebook of advanced data analysis methods for communication research (ss. 13-54). Sage Publications. https://doi.org/10.4135/9781452272054.n2
  • Preacher, K. J., & Hayes, A. F. (2008b). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879-891. https://doi.org/10.3758/BRM.40.3.879
  • Preacher, K. J., & Selig, J. P. (2012). Advantages of monte carlo confidence intervals for indirect effects. Communication Methods and Measures, 6(2), 77-98. https://doi.org/10.1080/19312458.2012.679848
  • Ramayah, T., Hwa, C., Chuah, F., Ting, H., & Memon, M. (2018). Partial least squares structural equation modeling (PLS-SEM) using SmartPLS 3.0: An updated and practical guide to statistical analysis (2nd edition). Pearson.
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There are 60 citations in total.

Details

Primary Language Turkish
Journal Section Review
Authors

Fatih Çelik 0000-0002-3765-5284

Publication Date December 26, 2022
Submission Date August 6, 2022
Published in Issue Year 2022

Cite

APA Çelik, F. (2022). Davranışsal İletişim Araştırmalarında Aracılık Testine Genel Bir Bakış. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi(49), 392-410. https://doi.org/10.52642/susbed.1158738


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