메뉴 건너뛰기




Volumn 18, Issue 8, 2013, Pages 1-14

Determining the number of factors to retain in EFA: Using the SPSS R-Menu v2.0 to make more judicious estimations

Author keywords

[No Author keywords available]

Indexed keywords


EID: 84886299055     PISSN: None     EISSN: 15317714     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (236)

References (32)
  • 1
    • 0001029742 scopus 로고
    • The sensitivity of confirmatory maximum likelihood factor analysis to violations of measurement scale and distributional assumptions
    • Babakus, E., Ferguson, C. E., & Joreskog, K. G. (1987). The sensitivity of confirmatory maximum likelihood factor analysis to violations of measurement scale and distributional assumptions. Journal of Marketing Research, 24, 222-228.
    • (1987) Journal of Marketing Research , vol.24 , pp. 222-228
    • Babakus, E.1    Ferguson, C.E.2    Joreskog, K.G.3
  • 2
    • 84886315223 scopus 로고    scopus 로고
    • Sourceforge.net. Retrieved December 11, 2012
    • Basto, M. (2012). SPSS R-Menu Files. Sourceforge.net. Retrieved December 11, 2012, from http://sourceforge.net/projects/spssrmenu/
    • (2012) SPSS R-Menu Files
    • Basto, M.1
  • 3
    • 84857398252 scopus 로고    scopus 로고
    • An SPSS R-Menu for Ordinal Factor Analysis
    • Basto, M., & Pereira, J. M. (2012). An SPSS R-Menu for Ordinal Factor Analysis. Journal of Statistical Software, 46(4), 1-29.
    • (2012) Journal of Statistical Software , vol.46 , Issue.4 , pp. 1-29
    • Basto, M.1    Pereira, J.M.2
  • 5
    • 84925929273 scopus 로고
    • Pearson's r and coarsely categorized measures
    • Bollen, K. A., & Barb, K. H. (1981). Pearson's r and coarsely categorized measures. American Sociological Review, 46, 232-239.
    • (1981) American Sociological Review , vol.46 , pp. 232-239
    • Bollen, K.A.1    Barb, K.H.2
  • 6
    • 84937549955 scopus 로고
    • The scree test for the number of factors
    • Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1, 245-276.
    • (1966) Multivariate Behavioral Research , vol.1 , pp. 245-276
    • Cattell, R.B.1
  • 8
    • 0039620968 scopus 로고    scopus 로고
    • Evaluating the use of exploratory factor analysis in psychological research
    • Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 3, 272-299.
    • (1999) Psychological Methods , vol.3 , pp. 272-299
    • Fabrigar, L.R.1    Wegener, D.T.2    MacCallum, R.C.3    Strahan, E.J.4
  • 9
    • 10844245499 scopus 로고    scopus 로고
    • An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data
    • Flora, D. B., & Curran, P. J. (2004). An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychological Methods, 9, 466-491.
    • (2004) Psychological Methods , vol.9 , pp. 466-491
    • Flora, D.B.1    Curran, P.J.2
  • 10
    • 79955563792 scopus 로고    scopus 로고
    • Performance of Velicer's Minimum Average Partial Factor Retention Method with Categorical Variables
    • Garrido, L. E., Abad, F. J., & Ponsoda, V. (2011). Performance of Velicer's Minimum Average Partial Factor Retention Method with Categorical Variables. Educational and Psychological Measurement, 71(3), 551-570.
    • (2011) Educational and Psychological Measurement , vol.71 , Issue.3 , pp. 551-570
    • Garrido, L.E.1    Abad, F.J.2    Ponsoda, V.3
  • 11
    • 84892456989 scopus 로고    scopus 로고
    • A new look at Horn's parallel analysis with ordinal variables
    • in press. Epub ahead of print retrieved December 10, 2012. doi:10.1037/a0030005
    • Garrido, L. E., Abad, F. J., & Ponsoda, V. (2012). A new look at Horn's parallel analysis with ordinal variables. Psychological Methods, in press. Epub ahead of print retrieved December 10, 2012. doi:10.1037/a0030005.
    • (2012) Psychological Methods
    • Garrido, L.E.1    Abad, F.J.2    Ponsoda, V.3
  • 13
    • 2342495760 scopus 로고    scopus 로고
    • Factor retention decisions in exploratory factor analysis: A tutorial on parallel analysis
    • Hayton, J. C., Allen, D. G., Scarpello, V. (2004). Factor retention decisions in exploratory factor analysis: A tutorial on parallel analysis. Organizational Research Methods, 7, 191-205.
    • (2004) Organizational Research Methods , vol.7 , pp. 191-205
    • Hayton, J.C.1    Allen, D.G.2    Scarpello, V.3
  • 14
    • 33646503263 scopus 로고    scopus 로고
    • Use of exploratory factor analysis in published research: common errors and some comment on improved practice
    • Henson, R. K., & Roberts, J. K. (2006). Use of exploratory factor analysis in published research: common errors and some comment on improved practice. Educational and Psychological Measurement, 66, 393-416.
    • (2006) Educational and Psychological Measurement , vol.66 , pp. 393-416
    • Henson, R.K.1    Roberts, J.K.2
  • 15
    • 72749123769 scopus 로고    scopus 로고
    • Polychoric verses Pearson correlations in exploratory and confirmatory factor analysis of ordinal variables
    • Holgado-Tello, F. P., Chacon-Moscoso, S., Barbero-Garcia, I., & Vila-Abad, E. (2010). Polychoric verses Pearson correlations in exploratory and confirmatory factor analysis of ordinal variables. Quality & Quantity, 44, 153-166.
    • (2010) Quality & Quantity , vol.44 , pp. 153-166
    • Holgado-Tello, F.P.1    Chacon-Moscoso, S.2    Barbero-Garcia, I.3    Vila-Abad, E.4
  • 16
    • 8644267207 scopus 로고
    • A rationale and test for the number of factors in factor analysis
    • Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30, 179-185.
    • (1965) Psychometrika , vol.30 , pp. 179-185
    • Horn, J.L.1
  • 17
    • 79952459161 scopus 로고    scopus 로고
    • IBM Corporation. IBM Corporation, Armonk, NY: IBM.
    • IBM Corporation (2010). IBM SPSS Statistics 19. IBM Corporation, Armonk, NY: IBM.
    • (2010) IBM SPSS Statistics 19
  • 18
    • 79952459161 scopus 로고    scopus 로고
    • IBM Corporation. IBM Corporation, Armonk, NY: IBM
    • IBM Corporation (2011). IBM SPSS Statistics 20. IBM Corporation, Armonk, NY: IBM.
    • (2011) IBM SPSS Statistics 20
  • 19
    • 79952459161 scopus 로고    scopus 로고
    • IBM Corporation. IBM Corporation, Armonk, NY: IBM
    • IBM Corporation (2012). IBM SPSS Statistics 21. IBM Corporation, Armonk, NY: IBM.
    • (2012) IBM SPSS Statistics 21
  • 20
    • 84976998771 scopus 로고
    • The application of electronic computers to factor analysis
    • Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational & Psychological Measurement, 20, 141-151.
    • (1960) Educational & Psychological Measurement , vol.20 , pp. 141-151
    • Kaiser, H.F.1
  • 21
    • 84893609004 scopus 로고    scopus 로고
    • Determining the number of factors to retain in EFA: An easy-to-use computer program for carrying out Parallel Analysis
    • Retrieved April 10, 2013, from
    • 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. Retrieved April 10, 2013, from http://pareonline.net/getvn.asp?v=12&n=2
    • (2007) Practical Assessment, Research & Evaluation , vol.12 , Issue.2 , pp. 1-11
    • Ledesma, R.D.1    Valero-Mora, P.2
  • 22
    • 0034242321 scopus 로고    scopus 로고
    • SPSS and SAS programs for determining the number of components using parallel analysis and Velicer's MAP test
    • O'Connor, B. P. (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.
    • (2000) Behavior Research Methods, Instruments, & Computers , vol.32 , pp. 396-402
    • O'Connor, B.P.1
  • 23
    • 0000541399 scopus 로고
    • Maximum likelihood estimation of the polychoric correlation coefficient
    • Olsson, U. (1979). Maximum likelihood estimation of the polychoric correlation coefficient. Psychometrika, 44, 443-460.
    • (1979) Psychometrika , vol.44 , pp. 443-460
    • Olsson, U.1
  • 24
    • 19044395321 scopus 로고    scopus 로고
    • How many principal components? Stopping rules for determining the number of non-trivial axes revisited
    • Peres-Neto, P. R., Jackson, D. A., & Somers, K. M. (2005). How many principal components? Stopping rules for determining the number of non-trivial axes revisited. Computational Statistics & Data Analysis, 49, 974-997.
    • (2005) Computational Statistics & Data Analysis , vol.49 , pp. 974-997
    • Peres-Neto, P.R.1    Jackson, D.A.2    Somers, K.M.3
  • 25
    • 0001139092 scopus 로고
    • Very simple structure - alternative procedure for estimating the optimal number of interpretable factors
    • Revelle, W., Rocklin, T. (1979). Very simple structure - alternative procedure for estimating the optimal number of interpretable factors. Multivariate Behavioral Research, 14(4), 403-414.
    • (1979) Multivariate Behavioral Research , vol.14 , Issue.4 , pp. 403-414
    • Revelle, W.1    Rocklin, T.2
  • 28
    • 84886312346 scopus 로고    scopus 로고
    • Tcnj.edu. Retrieved December 11, 2012, from
    • Ruscio, J. (2012). EFA with Comparison Data (R). Tcnj.edu. Retrieved December 11, 2012, from http://www.tcnj.edu/~ruscio/EFA%20Comparison%20Data.R
    • (2012) EFA with Comparison Data (R)
    • Ruscio, J.1
  • 29
    • 84866924945 scopus 로고    scopus 로고
    • Determining the number of factors to retain in an exploratory factor analysis using comparison data of a known factorial structure
    • Ruscio, J., & Roche, B. (2012). Determining the number of factors to retain in an exploratory factor analysis using comparison data of a known factorial structure. Psychological Assessment, 24(2), 282-292.
    • (2012) Psychological Assessment , vol.24 , Issue.2 , pp. 282-292
    • Ruscio, J.1    Roche, B.2
  • 30
    • 0001193215 scopus 로고
    • Determining the number of components from the matrix of partial correlations
    • Velicer, W. F. (1976). Determining the number of components from the matrix of partial correlations. Psychometrika, 41, 321-327.
    • (1976) Psychometrika , vol.41 , pp. 321-327
    • Velicer, W.F.1
  • 31
    • 0002366447 scopus 로고    scopus 로고
    • 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.)
    • Boston, MA: Kluwer Academic
    • 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 (pp. 41-71. Boston, MA: Kluwer Academic.
    • (2000) Problems and Solutions in Human Assessment: Honoring Douglas N. Jackson at Seventy , pp. 41-71
    • Velicer, W.F.1    Eaton, C.A.2    Fava, J.L.3
  • 32
    • 58149371334 scopus 로고
    • Comparison of five rules for determining the number of components to retain
    • Zwick, W. R., & Velicer, W. F. (1986). Comparison of five rules for determining the number of components to retain. Psychological Bulletin, 99, 432-442.
    • (1986) Psychological Bulletin , vol.99 , pp. 432-442
    • Zwick, W.R.1    Velicer, W.F.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.