Technical Brief
BibTex RIS Cite

Exploratory Factor Analysis with R Software

Year 2020, Volume: 4 Issue: 3, 276 - 293, 30.07.2020

Abstract

Exploratory Factor Analysis (EFA) is frequently used in educational and social sciences. EFA has been used in scale development and adaptation studies, in particular. Therefore, in this study, how to conduct EFA in R software has been explained. First of all, it is examined whether the data set holds the assumptions of EFA. When examining the assumptions of EFA, a function was written. Then, the number of factors was evaluated via parallel analysis (PA), minimum average partial (MAP), and scree plot. After deciding on the number of factors, EFA was conducted and reported. To report the results, R codes were provided to write the results in a Word document. Five categories and two-factorial data set were used in the current study. Oblimin was used as rotation method. Researchers should edit the R codes in terms of their data set properties.

References

  • Acar-Güvendir, M. ve Özer-Özkan, Y. (2015). Türkiye’deki eğitim alanında yayımlanan bilimsel dergilerde ölçek geliştirme ve uyarlama konulu makalelerin incelenmesi. Elektronik Sosyal Bilimler Dergisi, 14(52), 23–33. doi:10.17755/esosder.54872
  • Alpar, R. (2013). Uygulamalı çok değişkenli istatistiksel yöntemler (4. Baskı.). Ankara: Detay Yayıncılık.
  • Boztunç Öztürk, N., Eroğlu, M. G. ve Kelecioğlu, H. (2015). Eğitim alanında yapılan ölçek uyarlama makalelerinin incelenmesi. Eğitim ve Bilim, 40(178), 123–137. doi:10.15390/EB.2015.4091
  • Brown, T. A. (2015). Confirmatory factor analysis for applied research (2nd ed.). New York: The Guilford.
  • Buja, A. ve Eyuboglu, N. (1992). Remarks on parallel analysis. Multivariate Behavioral Research, 27(4), 509–540. doi:10.1207/s15327906mbr2704_2
  • Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1(2), 245–276. doi:10.1207/s15327906mbr0102_10
  • Cho, S.-J., Li, F. ve Bandalos, D. L. (2009). Accuracy of the parallel analysis procedure with polychoric correlations. Educational and Psychological Measurement, 69(5), 748–759. doi:10.1177/0013164409332229
  • Comrey, A. L. (1988). Factor-analytic methods of scale development in personality and clinical psychology. Journal of Consulting and Clinical Psychology, 56(5), 754–761. doi:10.1037/0022-006X.56.5.754
  • Costello, A. B. ve Osborne, J. W. (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research & Evaluation, 10(7), 27–29. doi:10.1.1.110.9154
  • Cota, A. A., Longman, R. S., Holden, R. R., Fekken, G. C. ve Xinaris, S. (1993). Interpolating 95th percentile eigenvalues from random data: An empirical example. Educational and Psychological Measurement, 53(3), 585–596. doi:10.1177/0013164493053003001
  • de Winter, J. C. F., Dodou, D. ve Wieringa, P. A. (2009). Exploratory factor analysis with small sample sizes. Multivariate Behavioral Research, 44(2), 147–181. doi:10.1080/00273170902794206
  • Enders, C. K. (2010). Applied missing data analysis. New York, NY: Guilford.
  • Erkuş, A. (2014). Psikolojide ölçme ve ölçek geliştirme-I: Temel kavramlar ve işlemler (2nd ed.). Ankara: Pegem Akademi.
  • Fabrigar, L. R. ve Wegener, D. T. (2012). Exploratory factor analysis. New York: Oxford University.
  • Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. ve Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. doi:10.1037/1082-989X.4.3.272
  • Floyd, F. J. ve Widaman, K. F. (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychological Assessment, 7(3), 286–299. doi:10.1037/1040-3590.7.3.286
  • Garrido, L. E., Abad, F. J. ve Ponsoda, V. (2011). Performance of Velicer’s minimum average partial factor retention method with categorical variables. Educational and Psychological Measurement, 71(3), 551–570. doi:10.1177/0013164410389489
  • Gorsuch, R. L. (1974). Factor analysis. Toronto: W. B. Saunders.
  • Guadagnoli, E. ve Velicer, W. F. (1988). Relation of sample size to the stability of component patterns. Psychological Bulletin, 103(2), 265–275.
  • Gül, Ş. ve Sözbilir, M. (2015). Fen ve matematik eğitimi alanında gerçekleştirilen ölçek geliştirme araştırmalarına yönelik tematik içerik analizi. Eğitim ve Bilim, 40(178), 85–102. doi:10.15390/EB.2015.4070
  • Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30(2), 179–185. doi:10.1007/BF02289447
  • Kahn, J. H. (2006). Factor analysis in counseling psychology research, training, practice: Principles, advances, and applications. The Counseling Psychologist, 34(5), 684–718. doi:10.1177/0011000006286347
  • Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20(1), 141–151. doi:10.1177/001316446002000116
  • Kaiser, H. F. ve Rice, J. (1974). Little Jiffy, Mark IV. Educational and Psychological Measurement, 34(1), 111–117. doi:10.1177/001316447403400115
  • Kılıç, A. F. ve Koyuncu, İ. (2017). Ölçek uyarlama çalışmalarının yapı geçerliği açısından incelenmesi. Ö. Demirel ve S. Dinçer (Ed.), Küreselleşen dünyada eğitim içinde (ss. 1202–1205). Ankara: Pegem Akademi.
  • Kline, P. (1994). An easy guide to factor analysis. Oxon: Routledge. doi:10.1016/0191-8869(94)90040-X
  • Kline, R. B. (2011). Principles and practise of structural equating modeling (3. Baskı.). New York: The Guilford Press.
  • Lorenzo-Seva, U. ve Ferrando, P. J. (2019). Factor (Version 10.10.01) [Computer software]. Tarragona: Universitat Rovira i Virgili.
  • Mardia, K. V. (1970). Measures of multivariate skewness and kurtosis with applications. Biometrika, 57(3), 519–530.
  • Osborne, J. W. (2014). Best practices in exploratory factor analysis. Best Practices in Quantitative Methods içinde (ss. 86–99).
  • Scotts Valley, CA: CreateSpace Independent Publishing. doi:10.4135/9781412995627.d8
  • Osborne, J. W. (2015). What is rotating in exploratory factor analysis? Practical Assessment Research & Evaluation, 20(2), 1–7.
  • Osborne, J. W. ve Banjanovic, E. S. (2016). Exploratory factor analysis with SAS®. Cary, NC: SAS Intitute Inc.
  • Osborne, J. W. ve Fitzpatrick, D. C. (2012). Replication analysis in exploratory factor analysis: What it is and why it makes your analysis better. Practical Assessment, Research & Evaluation, 17(15). http://pareonline.net/getvn.asp?v=17&n=15 adresinden erişildi.
  • Pearson, R. H. ve Mundform, D. J. (2010). Recommended sample size for conducting exploratory factor analysis on dichotomous data. Journal of Modern Applied Statistical Methods, 9(2), 359–368. doi:10.22237/jmasm/1288584240
  • Price, L. R. (2017). Psychometric methods: Theory and practice. New York, NY: The Guilford.
  • R Core Team. (2018). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.r-project.org/. adresinden erişildi.
  • Revelle, W. (2018). psych: Procedures for psychological, psychometric, and personality research. Evanston, Illinois. https://cran.r-project.org/package=psych adresinden erişildi.
  • Robitzsch, A. (2017). sirt: Supplementary item response theory models. https://cran.r-project.org/package=sirt adresinden erişildi.
  • Stevens, J. P. (2009). Applied multivariate statistics for the social science (5th ed.). New York: Taylor & Francis.
  • Stout, W. (1987). A nonparametric approach for assessing latent trait unidimensionality. Psychometrika, 52(4), 589–617. doi:10.1007/BF02294821
  • Streiner, D. L. (1994). Figuring out factors: The use and misuse of factor analysis. Canadian Journal of Psychiatry, 39(3), 135–140.
  • Tabachnik, B. G. ve Fidell, L. S. (2012). Using multivariate statistics (6th ed.). Boston: Pearson.
  • Velicer, W. F. (1976). The relation between factor score estimates, image scores, and principal component scores. Educational and Psychological Measurement, 36(1), 149–159. doi:10.1177/001316447603600114
  • Watkins, M. W. (2018). Exploratory factor analysis: A guide to best practice. Journal of Black Psychology, 44(3), 219–246. doi:10.1177/0095798418771807
  • Yang, Y. ve Xia, Y. (2015). On the number of factors to retain in exploratory factor analysis for ordered categorical data. Behavior Research Methods, 47(3), 756–772. doi:10.3758/s13428-014-0499-2
  • Zhang, J. (2007). Conditional covariance theory and DETECT for polytomous items. Psychometrika, 72(1), 69–91. doi:10.1007/s11336-004-1257-7
  • Zwick, W. R. ve Velicer, W. F. (1986). Comparison of five rules for determining the number of components to retain. Psychological Bulletin, 99(3), 432–442. doi:10.1037/0033-2909.99.3.432

R Yazılımı ile Açımlayıcı Faktör Analizi

Year 2020, Volume: 4 Issue: 3, 276 - 293, 30.07.2020

Abstract

Açımlayıcı Faktör Analizi (AFA) eğitim ve sosyal bilimler alanında sıklıkla kullanılmaktadır. AFA özellikle ölçek geliştirme ve uyarlama çalışmalarında kullanılmaktadır. Bu çalışmalarda AFA sıklıkla kullanıldığı için araştırmalacılar AFA’nın nasıl gerçekleştirildiğine ilişkin kılavuza ihtiyaç duyabilmektedir. Bu nedenle bu çalışmada AFA’nın R yazılımında nasıl gerçekleştirileceği açıklanmıştır. AFA farklı yazılımlarla da gerçekleştirilebilir. Fakat R yazılımı esnek ve ücretsizdir. Bu nedenle mevcut çalışma AFA’nın R yazılımında gerçekleştirilmesine odaklanmıştır. İlk olarak veri setinin AFA varsayımlarını sağlayıp sağlamadığı kontrol edilmiştir. Bunun için bir fonksiyon yazılmıştır. Daha sonra faktör sayısına karar vermek için Paralel Analiz (PA), en küçük kısmi ortalamalar (MAP) ve yamaç grafiği kullanılmıştır. Faktör sayısına karar verdikten sonra, açımlayıcı faktör analizi gerçekleştirilerek raporlanmıştır Sonuçların Word belgesi olarak raporlanması için gerekli R kodları sunulmuştur. Bu çalışmada beş kategorili (1-5) veri seti ile iki boyutlu yapı incelenmiştir. Faktör döndürme yöntemi olarak da eğik döndürme yöntmelerinden oblimin kullanılmıştır. Araştırmacılar R kodlarını kendi veri setlerinin özelliklerini göz önünde bulundurarak düzenlemelidir.

References

  • Acar-Güvendir, M. ve Özer-Özkan, Y. (2015). Türkiye’deki eğitim alanında yayımlanan bilimsel dergilerde ölçek geliştirme ve uyarlama konulu makalelerin incelenmesi. Elektronik Sosyal Bilimler Dergisi, 14(52), 23–33. doi:10.17755/esosder.54872
  • Alpar, R. (2013). Uygulamalı çok değişkenli istatistiksel yöntemler (4. Baskı.). Ankara: Detay Yayıncılık.
  • Boztunç Öztürk, N., Eroğlu, M. G. ve Kelecioğlu, H. (2015). Eğitim alanında yapılan ölçek uyarlama makalelerinin incelenmesi. Eğitim ve Bilim, 40(178), 123–137. doi:10.15390/EB.2015.4091
  • Brown, T. A. (2015). Confirmatory factor analysis for applied research (2nd ed.). New York: The Guilford.
  • Buja, A. ve Eyuboglu, N. (1992). Remarks on parallel analysis. Multivariate Behavioral Research, 27(4), 509–540. doi:10.1207/s15327906mbr2704_2
  • Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1(2), 245–276. doi:10.1207/s15327906mbr0102_10
  • Cho, S.-J., Li, F. ve Bandalos, D. L. (2009). Accuracy of the parallel analysis procedure with polychoric correlations. Educational and Psychological Measurement, 69(5), 748–759. doi:10.1177/0013164409332229
  • Comrey, A. L. (1988). Factor-analytic methods of scale development in personality and clinical psychology. Journal of Consulting and Clinical Psychology, 56(5), 754–761. doi:10.1037/0022-006X.56.5.754
  • Costello, A. B. ve Osborne, J. W. (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research & Evaluation, 10(7), 27–29. doi:10.1.1.110.9154
  • Cota, A. A., Longman, R. S., Holden, R. R., Fekken, G. C. ve Xinaris, S. (1993). Interpolating 95th percentile eigenvalues from random data: An empirical example. Educational and Psychological Measurement, 53(3), 585–596. doi:10.1177/0013164493053003001
  • de Winter, J. C. F., Dodou, D. ve Wieringa, P. A. (2009). Exploratory factor analysis with small sample sizes. Multivariate Behavioral Research, 44(2), 147–181. doi:10.1080/00273170902794206
  • Enders, C. K. (2010). Applied missing data analysis. New York, NY: Guilford.
  • Erkuş, A. (2014). Psikolojide ölçme ve ölçek geliştirme-I: Temel kavramlar ve işlemler (2nd ed.). Ankara: Pegem Akademi.
  • Fabrigar, L. R. ve Wegener, D. T. (2012). Exploratory factor analysis. New York: Oxford University.
  • Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. ve Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. doi:10.1037/1082-989X.4.3.272
  • Floyd, F. J. ve Widaman, K. F. (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychological Assessment, 7(3), 286–299. doi:10.1037/1040-3590.7.3.286
  • Garrido, L. E., Abad, F. J. ve Ponsoda, V. (2011). Performance of Velicer’s minimum average partial factor retention method with categorical variables. Educational and Psychological Measurement, 71(3), 551–570. doi:10.1177/0013164410389489
  • Gorsuch, R. L. (1974). Factor analysis. Toronto: W. B. Saunders.
  • Guadagnoli, E. ve Velicer, W. F. (1988). Relation of sample size to the stability of component patterns. Psychological Bulletin, 103(2), 265–275.
  • Gül, Ş. ve Sözbilir, M. (2015). Fen ve matematik eğitimi alanında gerçekleştirilen ölçek geliştirme araştırmalarına yönelik tematik içerik analizi. Eğitim ve Bilim, 40(178), 85–102. doi:10.15390/EB.2015.4070
  • Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30(2), 179–185. doi:10.1007/BF02289447
  • Kahn, J. H. (2006). Factor analysis in counseling psychology research, training, practice: Principles, advances, and applications. The Counseling Psychologist, 34(5), 684–718. doi:10.1177/0011000006286347
  • Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20(1), 141–151. doi:10.1177/001316446002000116
  • Kaiser, H. F. ve Rice, J. (1974). Little Jiffy, Mark IV. Educational and Psychological Measurement, 34(1), 111–117. doi:10.1177/001316447403400115
  • Kılıç, A. F. ve Koyuncu, İ. (2017). Ölçek uyarlama çalışmalarının yapı geçerliği açısından incelenmesi. Ö. Demirel ve S. Dinçer (Ed.), Küreselleşen dünyada eğitim içinde (ss. 1202–1205). Ankara: Pegem Akademi.
  • Kline, P. (1994). An easy guide to factor analysis. Oxon: Routledge. doi:10.1016/0191-8869(94)90040-X
  • Kline, R. B. (2011). Principles and practise of structural equating modeling (3. Baskı.). New York: The Guilford Press.
  • Lorenzo-Seva, U. ve Ferrando, P. J. (2019). Factor (Version 10.10.01) [Computer software]. Tarragona: Universitat Rovira i Virgili.
  • Mardia, K. V. (1970). Measures of multivariate skewness and kurtosis with applications. Biometrika, 57(3), 519–530.
  • Osborne, J. W. (2014). Best practices in exploratory factor analysis. Best Practices in Quantitative Methods içinde (ss. 86–99).
  • Scotts Valley, CA: CreateSpace Independent Publishing. doi:10.4135/9781412995627.d8
  • Osborne, J. W. (2015). What is rotating in exploratory factor analysis? Practical Assessment Research & Evaluation, 20(2), 1–7.
  • Osborne, J. W. ve Banjanovic, E. S. (2016). Exploratory factor analysis with SAS®. Cary, NC: SAS Intitute Inc.
  • Osborne, J. W. ve Fitzpatrick, D. C. (2012). Replication analysis in exploratory factor analysis: What it is and why it makes your analysis better. Practical Assessment, Research & Evaluation, 17(15). http://pareonline.net/getvn.asp?v=17&n=15 adresinden erişildi.
  • Pearson, R. H. ve Mundform, D. J. (2010). Recommended sample size for conducting exploratory factor analysis on dichotomous data. Journal of Modern Applied Statistical Methods, 9(2), 359–368. doi:10.22237/jmasm/1288584240
  • Price, L. R. (2017). Psychometric methods: Theory and practice. New York, NY: The Guilford.
  • R Core Team. (2018). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.r-project.org/. adresinden erişildi.
  • Revelle, W. (2018). psych: Procedures for psychological, psychometric, and personality research. Evanston, Illinois. https://cran.r-project.org/package=psych adresinden erişildi.
  • Robitzsch, A. (2017). sirt: Supplementary item response theory models. https://cran.r-project.org/package=sirt adresinden erişildi.
  • Stevens, J. P. (2009). Applied multivariate statistics for the social science (5th ed.). New York: Taylor & Francis.
  • Stout, W. (1987). A nonparametric approach for assessing latent trait unidimensionality. Psychometrika, 52(4), 589–617. doi:10.1007/BF02294821
  • Streiner, D. L. (1994). Figuring out factors: The use and misuse of factor analysis. Canadian Journal of Psychiatry, 39(3), 135–140.
  • Tabachnik, B. G. ve Fidell, L. S. (2012). Using multivariate statistics (6th ed.). Boston: Pearson.
  • Velicer, W. F. (1976). The relation between factor score estimates, image scores, and principal component scores. Educational and Psychological Measurement, 36(1), 149–159. doi:10.1177/001316447603600114
  • Watkins, M. W. (2018). Exploratory factor analysis: A guide to best practice. Journal of Black Psychology, 44(3), 219–246. doi:10.1177/0095798418771807
  • Yang, Y. ve Xia, Y. (2015). On the number of factors to retain in exploratory factor analysis for ordered categorical data. Behavior Research Methods, 47(3), 756–772. doi:10.3758/s13428-014-0499-2
  • Zhang, J. (2007). Conditional covariance theory and DETECT for polytomous items. Psychometrika, 72(1), 69–91. doi:10.1007/s11336-004-1257-7
  • Zwick, W. R. ve Velicer, W. F. (1986). Comparison of five rules for determining the number of components to retain. Psychological Bulletin, 99(3), 432–442. doi:10.1037/0033-2909.99.3.432
There are 48 citations in total.

Details

Primary Language English
Subjects Studies on Education
Journal Section Technical Note
Authors

Abdullah Faruk Kılıç 0000-0003-3129-1763

Publication Date July 30, 2020
Published in Issue Year 2020 Volume: 4 Issue: 3

Cite

APA Kılıç, A. F. (2020). Exploratory Factor Analysis with R Software. Anadolu Üniversitesi Eğitim Fakültesi Dergisi, 4(3), 276-293.
AMA Kılıç AF. Exploratory Factor Analysis with R Software. Anadolu Üniversitesi Eğitim Fakültesi Dergisi. July 2020;4(3):276-293.
Chicago Kılıç, Abdullah Faruk. “Exploratory Factor Analysis With R Software”. Anadolu Üniversitesi Eğitim Fakültesi Dergisi 4, no. 3 (July 2020): 276-93.
EndNote Kılıç AF (July 1, 2020) Exploratory Factor Analysis with R Software. Anadolu Üniversitesi Eğitim Fakültesi Dergisi 4 3 276–293.
IEEE A. F. Kılıç, “Exploratory Factor Analysis with R Software”, Anadolu Üniversitesi Eğitim Fakültesi Dergisi, vol. 4, no. 3, pp. 276–293, 2020.
ISNAD Kılıç, Abdullah Faruk. “Exploratory Factor Analysis With R Software”. Anadolu Üniversitesi Eğitim Fakültesi Dergisi 4/3 (July 2020), 276-293.
JAMA Kılıç AF. Exploratory Factor Analysis with R Software. Anadolu Üniversitesi Eğitim Fakültesi Dergisi. 2020;4:276–293.
MLA Kılıç, Abdullah Faruk. “Exploratory Factor Analysis With R Software”. Anadolu Üniversitesi Eğitim Fakültesi Dergisi, vol. 4, no. 3, 2020, pp. 276-93.
Vancouver Kılıç AF. Exploratory Factor Analysis with R Software. Anadolu Üniversitesi Eğitim Fakültesi Dergisi. 2020;4(3):276-93.

Education Faculty Journal - Anadolu University Journal of Education Faculty

Phone: +90 222 335 05 79          Fax: +90 222 335 05 73          E-mail: aujef@anadolu.edu.tr

Website: dergipark.org.tr/en/pub/aujef

ZZPdzvlpK9r_Df9C3M7j1rNRi7hhHRvPhlklJ3lfi5jk86Jd1s0Y5wcQ1QgbVaAP5Q=w300-rw  32GbAQWrubLZX4mVPClpLN0fRbAd3ru5BefccDAj7nKD8vz-_NzJ1ph_4WMYNefp3A=w300-rw  aYbdIM1abwyVSUZLDKoE0CDZGRhlkpsaPOg9tNnBktUQYsXflwknnOn2Ge1Yr7rImGk=w300-rw


by-nc-sa.png

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.