Year 2021, Volume 8 , Issue 3, Pages 542 - 552 2021-09-05

The Use of Exploratory Graph Analysis to Validate Trust in Relationships Scale

Akif AVCU [1]


Today, various methods have been developed with a purpose to determine the number of factors underlying a construct. However, there is no definitive agreement on which techniques to be preferred to extract the underlying dimensions. To this end, Exploratory Graphical Analysis (EGA), a recently proposed method, has been compared with traditional methods and the results have revealed that the EGA is less affected from conditions like sample size and inter-dimensional correlation. Besides, it provides more stable results across different conditions. Considering the attractive opportunities it offers, this method has taken its place in the literature as a remarkable alternative to traditional methods. The EGA provides unique outputs compared to other factor extraction techniques. Considering this, interpreting the results obtained within this new and promising framework is assumed to contribute to validation studies. Based on this reality, this study aims to apply the EGA method to Trust in Relations Scale (TRS) and therefore to contribute to its validity. The investigation of TRS’s reliability and validity has already been documented, presenting research opportunities to researchers in the field of positive psychology. The results revealed that, the EGA produces dimensionality structures identical to confirmatory factor analysis (CFA) and exploratory factor analysis (EFA). In addition, further psychometrical indicators within the framework of network analysis are provided. The findings of the study are believed to contribute to the validity of the already existing Trust in Relationships Scale.
trust in relationships, exploratory graph analysis, network psychometrics
  • Al-Salom, P., & Miller, C. J. (2017). The problem with online data collection: predicting invalid responding in undergraduate samples. Modern Psychological Studies, 22(2), 2. doi: 10.1007/s12144-017-9674-9
  • Al-Salom, P., & Miller, C. J. (2017). The problem with online data collection: predicting invalid responding in undergraduate samples. Modern Psychological Studies, 22(2), 2. doi: 10.1007/s12144-017-9674-9
  • Bandalos, D. L., & Boehm-Kaufman, M. R. (2009). Four common misconceptions in exploratory factor analysis. In C. E. Lance & R. J. Vandenberg (Eds.), Statistical and methodological myths and urban legends: Doctrine, verity and fable in the organizational and social sciences (p. 61–87). Routledge/Taylor & Francis Group.
  • Bandalos, D. L., & Boehm-Kaufman, M. R. (2009). Four common misconceptions in exploratory factor analysis. In C. E. Lance & R. J. Vandenberg (Eds.), Statistical and methodological myths and urban legends: Doctrine, verity and fable in the organizational and social sciences (p. 61–87). Routledge/Taylor & Francis Group.
  • Cattell, R. B. (1978). The scientific use of factor analysis in behavioral and life sciences. New York, NY: Plenum Press.
  • Cattell, R. B. (1978). The scientific use of factor analysis in behavioral and life sciences. New York, NY: Plenum Press.
  • Chen, J., Chen, Z., (2008). Extended Bayesian information criteria for model selection with large model spaces. Biometrika, 95, 759-771. doi: 10.1093/biomet/asn034
  • Chen, J., Chen, Z., (2008). Extended Bayesian information criteria for model selection with large model spaces. Biometrika, 95, 759-771. doi: 10.1093/biomet/asn034
  • Christensen, A. P., Golino, H. F., & Silvia, P. (2019). A psychometric network perspective on the measurement and assessment of personality traits. PsyArXiv. doi:10.31234/osf.io/ktejp.
  • Christensen, A. P., Golino, H. F., & Silvia, P. (2019). A psychometric network perspective on the measurement and assessment of personality traits. PsyArXiv. doi:10.31234/osf.io/ktejp.
  • Christensen, A. P., & Golino, H. (2021). On the equivalency of factor and network loadings. Behavior research methods, Advance online publication. doi:10.3758/s13428-020-01500-6
  • Christensen, A. P., & Golino, H. (2021). On the equivalency of factor and network loadings. Behavior research methods, Advance online publication. doi:10.3758/s13428-020-01500-6
  • Demirci, İ. & Ekşi. H. (2018). Keep calm and be happy: A mixed method study from character strengths to well-being. Educational Sciences: Theory & Practice, 18(29) 303–354. doi: 10.12738/estp.2018.2.0799
  • Demirci, İ. & Ekşi. H. (2018). Keep calm and be happy: A mixed method study from character strengths to well-being. Educational Sciences: Theory & Practice, 18(29) 303–354. doi: 10.12738/estp.2018.2.0799
  • Demirci, İ., Ekşi, H., Dinçer, D. ve Kardaş, S. (2017). Beş boyutlu iyi oluş modeli: PERMA Ölçeği’nin Türkçe formunun geçerlik ve güvenirliği. The Journal of Happiness & Well-Being, 5(1), 60-77.
  • Demirci, İ., Ekşi, H., Dinçer, D. ve Kardaş, S. (2017). Beş boyutlu iyi oluş modeli: PERMA Ölçeği’nin Türkçe formunun geçerlik ve güvenirliği. The Journal of Happiness & Well-Being, 5(1), 60-77.
  • Epskamp, S., & Fried, E.I. (2016). A tutorial on estimating regularized partial correlation networks. PsyArXiv.1607.01367.
  • Epskamp, S., & Fried, E.I. (2016). A tutorial on estimating regularized partial correlation networks. PsyArXiv.1607.01367.
  • Epskamp, S., Rhemtulla, M., Borsboom, D. (2017). Generalized network psychometrics: Combining network and latent variable models. Psychometrika, 82, 904-927. doi:10.1007/s11336-017-9557-x
  • Epskamp, S., Rhemtulla, M., Borsboom, D. (2017). Generalized network psychometrics: Combining network and latent variable models. Psychometrika, 82, 904-927. doi:10.1007/s11336-017-9557-x
  • Garcia-Garzon, E., Abad, F. J., & Garrido, L. E. (2019b). Searching for g: A new evaluation of spm-ls dimensionality. Journal of Intelligence, 7(3), 14. doi:10.3390/jintelligence7030014.
  • Garcia-Garzon, E., Abad, F. J., & Garrido, L. E. (2019b). Searching for g: A new evaluation of spm-ls dimensionality. Journal of Intelligence, 7(3), 14. doi:10.3390/jintelligence7030014.
  • Garrido, L. E., Abad, F. J., & Ponsoda, V. (2013). A new look at horn’s parallel analysis with ordinal variables. Psychological Methods, 18(4), 454–74. doi:10.1037/a0030005
  • Garrido, L. E., Abad, F. J., & Ponsoda, V. (2013). A new look at horn’s parallel analysis with ordinal variables. Psychological Methods, 18(4), 454–74. doi:10.1037/a0030005
  • Golino, H., & Christensen, A. P. (2020). EGAnet: Exploratory Graph Analysis -- A framework for estimating the number of dimensions in multivariate data using network psychometrics. R package version 0.9.4.
  • Golino, H., & Christensen, A. P. (2020). EGAnet: Exploratory Graph Analysis -- A framework for estimating the number of dimensions in multivariate data using network psychometrics. R package version 0.9.4.
  • Golino, H. F., & Epskamp, S. (2017). Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research. PloS One, 12(6), e0174035. doi:10.1371/journal.pone.0174035
  • Golino, H. F., & Epskamp, S. (2017). Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research. PloS One, 12(6), e0174035. doi:10.1371/journal.pone.0174035
  • Golino, H., Shi, D., Garrido, L.E., Christensen, A.P., Nieto, M.D., Sadana, R., Thiyagarajan, J.A. & Martinez-Molina, A. (2018, December 19). Investigating the performance of Exploratory Graph Analysis and traditional techniques to identify the number of latent factors: A simulation and tutorial. doi:10.31234/osf.io/gzcre
  • Golino, H., Shi, D., Garrido, L.E., Christensen, A.P., Nieto, M.D., Sadana, R., Thiyagarajan, J.A. & Martinez-Molina, A. (2018, December 19). Investigating the performance of Exploratory Graph Analysis and traditional techniques to identify the number of latent factors: A simulation and tutorial. doi:10.31234/osf.io/gzcre
  • Guttman, L. (1954). Some necessary conditions for common factor analysis. Psychometrika, 19, 149-161.doi: 10.1007/BF02289162
  • Guttman, L. (1954). Some necessary conditions for common factor analysis. Psychometrika, 19, 149-161.doi: 10.1007/BF02289162
  • 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
  • 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
  • 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. (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20(1), 141–151. doi:10.1177/001316446002000116
  • Keith, T. Z., Caemmerer, J. M. & Reynolds, M. R. (2016). Comparison of methods for factor extraction for cognitive test-like data: Which overfactor, which underfactor? Intelligence, 54, 37-54. doi:10.1016/j.intell.2015.11.003
  • Keith, T. Z., Caemmerer, J. M. & Reynolds, M. R. (2016). Comparison of methods for factor extraction for cognitive test-like data: Which overfactor, which underfactor? Intelligence, 54, 37-54. doi:10.1016/j.intell.2015.11.003
  • Lauritzen, S. L. (1996b). Graphical Models. Oxford Statistical Science Series. volume 17. New York, NY: Oxford University Press.
  • Lauritzen, S. L. (1996b). Graphical Models. Oxford Statistical Science Series. volume 17. New York, NY: Oxford University Press.
  • Ledesma, R. D., & Valero-Mora, P. (2007). Determining the Number of Factors to Retain in EFA: an easy-to-use computer program for carrying out Parallel Analysis. Practical Assessment, Research & Evaluation, 12(2), 1-11. doi:10.7275/wjnc-nm63
  • Ledesma, R. D., & Valero-Mora, P. (2007). Determining the Number of Factors to Retain in EFA: an easy-to-use computer program for carrying out Parallel Analysis. Practical Assessment, Research & Evaluation, 12(2), 1-11. doi:10.7275/wjnc-nm63
  • Lubbe, D. (2019). Parallel analysis with categorical variables: Impact of category probability proportions on dimensionality assessment accuracy. Psychological Methods, 24(3), 339–351. doi: 10.1037/met0000171.
  • Lubbe, D. (2019). Parallel analysis with categorical variables: Impact of category probability proportions on dimensionality assessment accuracy. Psychological Methods, 24(3), 339–351. doi: 10.1037/met0000171.
  • Osborne J.W. & Costello (2009). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Pan-Pacific Management Review, 12(2):131-146.
  • Osborne J.W. & Costello (2009). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Pan-Pacific Management Review, 12(2):131-146.
  • Osborne, J., Costello, A. & Kellow, J. (2008). Best practices in exploratory factor analysis. In Osborne, J. (Ed.), Best practices in quantitative methods (pp. 86-99). SAGE Publications, Inc., doi:10.4135/9781412995627
  • Osborne, J., Costello, A. & Kellow, J. (2008). Best practices in exploratory factor analysis. In Osborne, J. (Ed.), Best practices in quantitative methods (pp. 86-99). SAGE Publications, Inc., doi:10.4135/9781412995627
  • Pons, P., & Latapy, M. (2006). Computing communities in large networks using random walks. Journal of Graph Algorithms and Applications, 10, 191–218. doi: 10.7155/jgaa.00185
  • Pons, P., & Latapy, M. (2006). Computing communities in large networks using random walks. Journal of Graph Algorithms and Applications, 10, 191–218. doi: 10.7155/jgaa.00185
  • R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
  • R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
  • Raîche, G., Walls, T. A., Magis, D., Riopel, M., & Blais, J.-G. (2013). Non-graphical solutions for Cattell’s scree test. Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 9(1), 23–29. doi:10.1027/1614-2241/a000051
  • Raîche, G., Walls, T. A., Magis, D., Riopel, M., & Blais, J.-G. (2013). Non-graphical solutions for Cattell’s scree test. Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 9(1), 23–29. doi:10.1027/1614-2241/a000051
  • Rosseel, Y. (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36. doi: 10.18637/jss.v048.i02
  • Rosseel, Y. (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36. doi: 10.18637/jss.v048.i02
  • Spearman, C. (1904). "General intelligence" objectively determined and measured. American Journal of Psychology, 15, 201–293. doi: 10.2307/1412107
  • Spearman, C. (1904). "General intelligence" objectively determined and measured. American Journal of Psychology, 15, 201–293. doi: 10.2307/1412107
  • Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society: Series B, 267–288.
  • Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society: Series B, 267–288.
  • Timmerman, M. E., & Lorenzo-Seva, U. (2011). Dimensionality assessment of ordered polytomous items with parallel analysis. Psychological Methods, 16(2), 209–220. doi: 10.1037/a0023353
  • Timmerman, M. E., & Lorenzo-Seva, U. (2011). Dimensionality assessment of ordered polytomous items with parallel analysis. Psychological Methods, 16(2), 209–220. doi: 10.1037/a0023353
  • van Borkulo, C. D., Borsboom, D., Epskamp, S., Blanken, T. F., Boschloo, L., Schoevers, R. A., & Waldorp, L. J. (2014). A new method for constructing networks from binary data. Scientific Reports, 4, [5918]. doi: 10.1038/srep05918.
  • van Borkulo, C. D., Borsboom, D., Epskamp, S., Blanken, T. F., Boschloo, L., Schoevers, R. A., & Waldorp, L. J. (2014). A new method for constructing networks from binary data. Scientific Reports, 4, [5918]. doi: 10.1038/srep05918.
  • Velicer, W. F. (1976). Determining the number of components from the matrix of partial correlations. Psychometrika, 41(3), 321–327. doi: 10.1007/BF02293557
  • Velicer, W. F. (1976). Determining the number of components from the matrix of partial correlations. Psychometrika, 41(3), 321–327. doi: 10.1007/BF02293557
  • Velicer, W. F., Eaton, C. A., & Fava, J. L. (2000). Construct explication through factor or component analysis: A review and evaluation of alternative procedures for determining the number of factors or components. In R. D.
  • Velicer, W. F., Eaton, C. A., & Fava, J. L. (2000). Construct explication through factor or component analysis: A review and evaluation of alternative procedures for determining the number of factors or components. In R. D.
  • Goffin & E. Helmes (Eds.), Problems and solutions in human assessment: Honoring Douglas N. Jackson at seventy (p. 41–71). Kluwer Academic/Plenum Publishers. doi: 10.1007/978-1-4615-4397-8_3.
  • Goffin & E. Helmes (Eds.), Problems and solutions in human assessment: Honoring Douglas N. Jackson at seventy (p. 41–71). Kluwer Academic/Plenum Publishers. doi: 10.1007/978-1-4615-4397-8_3.
Primary Language en
Subjects Education, Scientific Disciplines
Published Date September
Journal Section Articles
Authors

Orcid: 0000-0003-1977-7592
Author: Akif AVCU (Primary Author)
Institution: Marmara University
Country: Turkey


Dates

Publication Date : September 5, 2021

APA Avcu, A . (2021). The Use of Exploratory Graph Analysis to Validate Trust in Relationships Scale . International Journal of Assessment Tools in Education , 8 (3) , 542-552 . DOI: 10.21449/ijate.831784