A Review of Exploratory Factor Analysis Decisions and Overview of Current Practices: What We Are Doing and How Can We Improve?

International Journal of Human-Computer Interaction

Volumn 32, Issue 1, 2016, Pages 51-62

  Howard, Matt C ^a  

^a PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

HUMAN COMPUTER INTERACTION; MULTIVARIANT ANALYSIS;

ANALYTIC METHOD; COMPUTER INTERACTION; CURRENT PRACTICES; DIRECT SOLUTION; EXPLORATORY FACTOR ANALYSIS; EXPLORATORY FACTOR ANALYSIS (EFA); FACTOR ROTATION; INSPECTION TECHNIQUE;

FACTOR ANALYSIS;

EID: 84953320814     PISSN: 10447318     EISSN: 15327590     Source Type: Journal    
DOI: 10.1080/10447318.2015.1087664     Document Type: Article

References (60)

1. J.R.Baker,, & S.M.Moore, (2011). Creation and validation of the personal blogging style scale. Cyberpsychology, Behavior, and Social Networking, 14, 379–385.
2. M.S.Bartlett, (1950). Tests of significance in factor analysis. British Journal of Statistical Psychology, 3, 77–85.
3. Y.Benjamini,, & Y.Hochberg, (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 289–300.
4. P.M.Bentler,, & Y.Kano, (1990). On the equivalence of factors and components. Multivariate Behavioral Research, 25, 67–74.
5. M.W.Browne, (2001). An overview of analytic rotation in exploratory factor analysis. Multivariate Behavioral Research, 36, 111–150.
6. U.Bunz, (2004). The computer-email-web (CEW) fluency scale-development and validation. International Journal of Human–Computer Interaction, 17, 479–506.
7. S.E.Caplan, (2002). Problematic Internet use and psychosocial well-being: Development of a theory-based cognitive–behavioral measurement instrument. Computers in Human Behavior, 18, 553–575.
8. B.Çetin,, E.Yaman,, & A.Peker, (2011). Cyber victim and bullying scale: A study of validity and reliability. Computers & Education, 57, 2261–2271.
9. J.P.Charlton,, & P.E.Birkett, (1995). The development and validation of the Computer Apathy and Anxiety Scale. Journal of Educational Computing Research, 13, 41–59.
10. N.Cliff, (1988). The eigenvalues-greater-than-one rule and the reliability of components. Psychological Bulletin, 103, 276–279.
11. A.L.Comrey, & H.B.Lee (1992). A first course in factor analysis. Hillsdale, NJ: Erlbaum.
12. J.M.Conway,, & A.I.Huffcutt, (2003). A review and evaluation of exploratory factor analysis practices in organizational research. Organizational Research Methods, 6, 147–168.
13. A.B.Costello,, & J.Osborne, (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research & Evaluation, 10, 1–9.
14. R.Cudeck, (2000). Exploratory factor analysis. Handbook of Applied Multivariate Statistics and Mathematical Modeling, pp. 265–296.
15. E.E.Cureton,, & S.A.Mulaik, (1975). The weighted varimax rotation and the promax rotation. Psychometrika, 40, 183–195.
16. J.C.De Winter,, & D.Dodou, (2012). Factor recovery by principal axis factoring and maximum likelihood factor analysis as a function of factor pattern and sample size. Journal of Applied Statistics, 39, 695–710.
17. C.D.Dziuban,, & C.W.Harris, (1973). On the extraction of components and the applicability of the factor model. American Educational Research Journal, 10, 93–99.
18. C.D.Dziuban,, & E.C.Shirkey, (1974). When is a correlation matrix appropriate for factor analysis? Some decision rules. Psychological Bulletin, 81, 358–361.
19. L.R.Fabrigar,, & D.T.Wegener, (2012). Understanding statistics: Exploratory factor analysis. New York, NY: Oxford University.
20. L.R.Fabrigar,, D.T.Wegener,, R.C.MacCallum,, & E.J.Strahan, (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4, 272–299.
21. A.Faiola,, C.C.Ho,, M.D.Tarrant,, & K.F.MacDorman, (2011). The aesthetic dimensions of US and South Korean responses to web home pages: A cross-cultural comparison. International Journal of Human–Computer Interaction, 27, 131–150.
22. J.K.Ford,, R.C.MacCallum,, & M.Tail, (1986). The applications of exploratory factor analysis in applied psychology: A critical review and analysis. Personnel Psychology, 39, 291–314.
23. M.Furr, (2011). Scale construction and psychometrics for social and personality psychology. Thousand Oaks, CA: Sage.
24. R.L.Gorsuch, (1988). Exploratory factor analysis. In J. R. Nesselroade & R. B. Cattell (Eds.), Handbook of multivariate experimental psychology (pp. 231–258). New York, NY: Springer.
25. R.L.Gorsuch, (1997). Exploratory factor analysis: Its role in item analysis. Journal of Personality Assessment, 68, 532–560.
26. J.F.Hair,, W.C.Black,, B.J.Babin,, R.E.Anderson,, & R.L.Tatham, (2006). Multivariate data analysis (Vol. 6). Upper Saddle River, NJ: Pearson Prentice Hall.
27. J.Hamari,, & J.Koivisto, (2014). Measuring flow in gamification: Dispositional Flow Scale–2. Computers in Human Behavior, 40, 133–143.
28. J.C.Hayton,, D.G.Allen,, & V.Scarpello, (2004). Factor retention decisions in exploratory factor analysis: A tutorial on parallel analysis. Organizational Research Methods, 7, 191–205.
29. R.K.Henson,, & J.K.Roberts, (2006). Use of exploratory factor analysis in published research common errors and some comment on improved practice. Educational and Psychological Measurement, 66, 393–416.
30. T.R.Hinkin, (1995). A review of scale development practices in the study of organizations. Journal of Management, 21, 967–988.
31. T.R.Hinkin, (1998). A brief tutorial on the development of measures for use in survey questionnaires. Organizational Research Methods, 1, 104–121.
32. J.L.Horn, (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30, 179–185.
33. M.C.Howard, (2014). Creation of a computer self-efficacy measure: Analysis of internal consistency, psychometric properties, and validity. Cyberpsychology, Behavior, and Social Networking, 17, 677–681.
34. M.C.Howard,, & B.S.Jayne, (2015). An analysis of more than 1,400 articles, 900 scales, and 17 years of research: The state of scales in cyberpsychology, behavior, and social networking. Cyberpsychology, Behavior, and Social Networking, 18, 181–187.
35. R.I.Jennrich,, & P.F.Sampson, (1966). Rotation for simple loadings. Psychometrika, 31, 313–323.
36. H.F.Kaiser, (1958). The varimax criterion for analytic rotation in factor analysis. Psychometrika, 23, 187–200.
37. H.F.Kaiser, (1960). The application of electronic computers to factor analysis. Educational and Psychological Measurement, 20, 141–151.
38. H.F.Kaiser, (1970). A second generation little jiffy. Psychometrika, 35, 401–415.
39. P.Kline, (2014). An easy guide to factor analysis. New York, NY: Routledge.
40. S.Korobili,, A.Togia,, & A.Malliari, (2010). Computer anxiety and attitudes among undergraduate students in Greece. Computers in Human Behavior, 26, 399–405.
41. L.T.Lam,, & Y.Li, (2013). The validation of the R-victimisation scale (E-VS) and the E-bullying scale (E-BS) for adolescents. Computers in Human Behavior, 29, 3–7.
42. R.C.MacCallum,, K.F.Widaman,, S.Zhang,, & S.Hong, (1999). Sample size in factor analysis. Psychological Methods, 4, 84–99.
43. A.G.Namlu,, & H.F.Odabasi, (2007). Unethical computer using behavior scale: A study of reliability and validity on Turkish university students. Computers & Education, 48, 205–215.
44. B.P.O’Connor, (2000). SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s MAP test. Behavior Research Methods, Instruments, & Computers, 32, 396–402.
45. S.Ozkan,, & R.Koseler, (2009). Multidimensional students’ evaluation of e-learning systems in the higher education context: An empirical investigation. Computers & Education, 53, 1285–1296.
46. Patil, V. H., Singh, S. N., Mishra, S., & Donavan D. T. (2007). Parallel analysis engine to aid determining number of factors to retain [Computer software]. Available from http://smishra.faculty.ku.edu/parallelengine.htm
47. V.H.Patil,, S.N.Singh,, S.Mishra,, & D.T.Donavan (2008). Efficient theory development and factor retention criteria: A case for abandoning the ‘eigenvalue greater than one’ criterion. Journal of Business Research, 61, 162–170.
48. M.Pawlikowski,, C.Altstötter-Gleich,, & M.Brand, (2013). Validation and psychometric properties of a short version of Young’s Internet Addiction Test. Computers in Human Behavior, 29, 1212–1223.
49. K.J.Preacher,, & R.C.MacCallum, (2003). Repairing Tom Swift’s electric factor analysis machine. Understanding Statistics: Statistical Issues in Psychology, Education, and the Social Sciences, 2, 13–43.
50. H.Qin,, P.L.P.Rau,, & G.Salvendy, (2009). Measuring player immersion in the computer game narrative. International Journal of Human–Computer Interaction, 25, 107–133.
51. R.K.Rainer,, & M.D.Miller, (1996). An assessment of the psychometric properties of the computer attitude scale. Computers in Human Behavior, 12, 93–105.
52. B.G.Tabachnick,, & L.S.Fidell, (2001). Using multivariate statistics. Boston, MA: Allyn & Bacon.
53. B.G.Tabachnick,, & L.S.Fidell, (2007). Using multivariate statistics (5th ed.). Boston, MA: Allyn & Bacon.
54. S.Tobias,, & J.E.Carlson, (1969). Brief report: Bartlett’s test of sphericity and chance findings in factor analysis. Multivariate Behavioral Research, 4, 375–377.
55. J.van Braak,, & P.Tearle, (2007). The computer attributes for learning scale (CALS) among university students: Scale development and relationship with actual computer use for learning. Computers in Human Behavior, 23, 2966–2982.
56. W.F.Velicer,, & J.L.Fava, (1998). Effects of variable and subject sampling on factor pattern recovery. Psychological Methods, 3, 231–251.
57. T.Yang,, J.Linder,, & D.Bolchini, (2012). DEEP: design-oriented evaluation of perceived usability. International Journal of Human–Computer Interaction, 28, 308–346.
58. K.A.Yeomans,, & P.A.Golder, (1982). The Guttman-Kaiser criterion as a predictor of the number of common factors. The Statistician, pp. 221–229.
59. K.W.Zoski,, & S.Jurs, (1996). An objective counterpart to the visual scree test for factor analysis: The standard error scree. Educational and Psychological Measurement, 56, 443–451.
60. W.R.Zwick,, & W.F.Velicer, (1986). Comparison of five rules for determining the number of components to retain. Psychological Bulletin, 99, 432–442.