-
1
-
-
85060294482
-
How to determine the number of factors to retain in exploratory factor analysis: A comparison of extraction methods under realistic conditions
-
Auerswald M., Moshagen M., (2019). How to determine the number of factors to retain in exploratory factor analysis: A comparison of extraction methods under realistic conditions. Psychological Methods, 24(4), 468-491. https://doi.org/10.1037/met0000200
-
(2019)
Psychological Methods
, vol.24
, Issue.4
, pp. 468-491
-
-
Auerswald, M.1
Moshagen, M.2
-
2
-
-
79957827711
-
Sparse Bayesian infinite factor models
-
Bhattacharya A., Dunson D. B., (2011). Sparse Bayesian infinite factor models. Biometrika, 98(2), 291-306. https://doi.org/10.1093/biomet/asr013
-
(2011)
Biometrika
, vol.98
, Issue.2
, pp. 291-306
-
-
Bhattacharya, A.1
Dunson, D.B.2
-
3
-
-
0007456042
-
Bayesian factor analysis model and choosing the number of factors using a new informational complexity criterion
-
Rizzi A., Vichi M., Bock H.H., (eds), (Eds.), (., -,). Springer
-
Bozdogan H., Shigemasu K., (1998). Bayesian factor analysis model and choosing the number of factors using a new informational complexity criterion. In Rizzi A., Vichi M., Bock H. H., (Eds.), Advances in data science and classification. Studies in classification, data analysis, and knowledge organization (pp. 335-342). Springer. https://doi.org/10.1007/978-3-642-72253-0_45
-
(1998)
Advances in data science and classification. Studies in classification, data analysis, and knowledge organization
, pp. 335-342
-
-
Bozdogan, H.1
Shigemasu, K.2
-
4
-
-
0000626398
-
Remarks on parallel analysis
-
Buja A., Eyuboglu N., (1992). Remarks on parallel analysis. Multivariate Behavioral Research, 27(4), 509-540. https://doi.org/10.1207/s15327906mbr2704_2
-
(1992)
Multivariate Behavioral Research
, vol.27
, Issue.4
, pp. 509-540
-
-
Buja, A.1
Eyuboglu, N.2
-
5
-
-
84908248026
-
Bayesian exploratory factor analysis
-
Conti G., Frühwirth-Schnatter S., Heckman J. J., Piatek R., (2014). Bayesian exploratory factor analysis. Journal of Econometrics, 183(1), 31-57. https://doi.org/10.1016/j.jeconom.2014.06.008
-
(2014)
Journal of Econometrics
, vol.183
, Issue.1
, pp. 31-57
-
-
Conti, G.1
Frühwirth-Schnatter, S.2
Heckman, J.J.3
Piatek, R.4
-
6
-
-
0037262421
-
A review and evaluation of exploratory factor analysis practices in organizational research
-
Conway J. M., Huffcutt A. I., (2003). A review and evaluation of exploratory factor analysis practices in organizational research. Organizational research methods, 6(2), 147-168. https://doi.org/10.1177/1094428103251541
-
(2003)
Organizational research methods
, vol.6
, Issue.2
, pp. 147-168
-
-
Conway, J.M.1
Huffcutt, A.I.2
-
7
-
-
77957942372
-
Evaluation of parallel analysis methods for determining the number of factors
-
Crawford A., Green S. B., Levy R., Lo W-J, Scott L, Svetina D., Thompson M. S., (2010). Evaluation of parallel analysis methods for determining the number of factors. Educational and Psychological Measurement, 70(6), 885-901. https://doi.org/10.1177/0013164410379332
-
(2010)
Educational and Psychological Measurement
, vol.70
, Issue.6
, pp. 885-901
-
-
Crawford, A.1
Green, S.B.2
Levy, R.3
Lo, W.-J.4
Scott, L.5
Svetina, D.6
Thompson, M.S.7
-
8
-
-
31644441157
-
Using confirmatory factor analysis for construct validation: An empirical review
-
DiStefano C., Hess B., (2005). Using confirmatory factor analysis for construct validation: An empirical review. Journal of Psychoeducational Assessment, 23(3), 225-241. https://doi.org/10.1177/073428290502300303
-
(2005)
Journal of Psychoeducational Assessment
, vol.23
, Issue.3
, pp. 225-241
-
-
DiStefano, C.1
Hess, B.2
-
9
-
-
0039620968
-
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, 4(3), 272-299. https://doi.org/10.1037/1082-989X.4.3.272
-
(1999)
Psychological Methods
, vol.4
, Issue.3
, pp. 272-299
-
-
Fabrigar, L.R.1
Wegener, D.T.2
MacCallum, R.C.3
Strahan, E.J.4
-
10
-
-
85021394779
-
The applications of exploratory factor analysis in applied psychology: A critical review and analysis
-
Ford J. K., MacCallum R. C., Tait M., (1986). The applications of exploratory factor analysis in applied psychology: A critical review and analysis. Personnel Psychology, 39(2), 291-314. https://doi.org/10.1111/j.1744-6570.1986.tb00583.x
-
(1986)
Personnel Psychology
, vol.39
, Issue.2
, pp. 291-314
-
-
Ford, J.K.1
MacCallum, R.C.2
Tait, M.3
-
11
-
-
25444484077
-
Posterior predictive assessment of model fitness via realized discrepancies
-
Gelman A., Meng X. L., Stern H., (1996). Posterior predictive assessment of model fitness via realized discrepancies. Statistica Sinica, 6(4), 733-807. https://www.jstor.org/stable/24306036
-
(1996)
Statistica Sinica
, vol.6
, Issue.4
, pp. 733-807
-
-
Gelman, A.1
Meng, X.L.2
Stern, H.3
-
12
-
-
0030539706
-
Measuring the pricing error of the arbitrage pricing theory
-
Geweke J., Zhou G., (1996). Measuring the pricing error of the arbitrage pricing theory. Review of Financial Studies, 9(2), 557-587. https://doi.org/10.1093/rfs/9.2.557
-
(1996)
Review of Financial Studies
, vol.9
, Issue.2
, pp. 557-587
-
-
Geweke, J.1
Zhou, G.2
-
13
-
-
84973751080
-
An improvement on Horn’s parallel analysis methodology for selecting the correct number of factors to retain
-
Glorfeld L. W., (1995). An improvement on Horn’s parallel analysis methodology for selecting the correct number of factors to retain. Educational and Psychological Measurement, 55(3), 377-393. https://doi.org/10.1177/0013164495055003002
-
(1995)
Educational and Psychological Measurement
, vol.55
, Issue.3
, pp. 377-393
-
-
Glorfeld, L.W.1
-
14
-
-
84864816565
-
A proposed solution to the problem with using completely random data to assess the number of factors with parallel analysis
-
Green S. B., Levy R., Thompson M. S., Lu M., Lo W.-J., (2012). A proposed solution to the problem with using completely random data to assess the number of factors with parallel analysis. Educational and Psychological Measurement, 72(3), 357-374. https://doi.org/10.1177/0013164411422252
-
(2012)
Educational and Psychological Measurement
, vol.72
, Issue.3
, pp. 357-374
-
-
Green, S.B.1
Levy, R.2
Thompson, M.S.3
Lu, M.4
Lo, W.-J.5
-
15
-
-
84953432963
-
Accuracy of revised and traditional parallel analyses for assessing dimensionality with binary data
-
Green S. B., Redell N., Thompson M. S., Levy R., (2016). Accuracy of revised and traditional parallel analyses for assessing dimensionality with binary data. Educational and Psychological Measurement, 76(1), 5-21. https://doi.org/10.1177/0013164415581898
-
(2016)
Educational and Psychological Measurement
, vol.76
, Issue.1
, pp. 5-21
-
-
Green, S.B.1
Redell, N.2
Thompson, M.S.3
Levy, R.4
-
16
-
-
84988305981
-
Type I and II error rates and overall accuracy of the revised parallel analysis method for determining the number of factors
-
Green S. B., Thompson M. S., Levy R., Lo W.-J., (2015). Type I and II error rates and overall accuracy of the revised parallel analysis method for determining the number of factors. Educational and Psychological Measurement, 75(3), 428-457. https://doi.org/10.1177/0013164414546566
-
(2015)
Educational and Psychological Measurement
, vol.75
, Issue.3
, pp. 428-457
-
-
Green, S.B.1
Thompson, M.S.2
Levy, R.3
Lo, W.-J.4
-
17
-
-
85043360768
-
Relative accuracy of two parallel analysis methods that use the proper reference distribution
-
Green S. B., Xu Y., Thompson M. S., (2017). Relative accuracy of two parallel analysis methods that use the proper reference distribution. Educational and Psychological Measurement, 78(4), 589-604. https://doi.org/10.1177/0013164417718610
-
(2017)
Educational and Psychological Measurement
, vol.78
, Issue.4
, pp. 589-604
-
-
Green, S.B.1
Xu, Y.2
Thompson, M.S.3
-
18
-
-
85088377318
-
-
May, Determining the number of factors by comparing real with random data: A serious flaw and some possible corrections, Annual meeting of the Classification Society of North America, Philadelphia, PA, United States, (,)., [Paper presentation]
-
Harshman R. A., Reddon J. R., (1983, May). Determining the number of factors by comparing real with random data: A serious flaw and some possible corrections [Paper presentation]. Annual meeting of the Classification Society of North America, Philadelphia, PA, United States.
-
(1983)
-
-
Harshman, R.A.1
Reddon, J.R.2
-
19
-
-
2342495760
-
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(2), 191-205. https://doi.org/10.1177/1094428104263675
-
(2004)
Organizational Research Methods
, vol.7
, Issue.2
, pp. 191-205
-
-
Hayton, J.C.1
Allen, D.G.2
Scarpello, V.3
-
21
-
-
0010017776
-
Note on a criterion for the number of common factors
-
Humphreys L. G., Ilgen D. R., (1969). Note on a criterion for the number of common factors. Educational and Psychological Measurement, 29(3), 571-578. https://doi.org/10.1177/001316446902900303
-
(1969)
Educational and Psychological Measurement
, vol.29
, Issue.3
, pp. 571-578
-
-
Humphreys, L.G.1
Ilgen, D.R.2
-
22
-
-
85057289936
-
Bayesian estimation of sparse dynamic factor models with order-independent and ex-post mode identification
-
Kaufmann S., Schumacher C., (2019). Bayesian estimation of sparse dynamic factor models with order-independent and ex-post mode identification. Journal of Econometrics, 210(1), 116-134. https://doi.org/10.1016/j.jeconom.2018.11.008
-
(2019)
Journal of Econometrics
, vol.210
, Issue.1
, pp. 116-134
-
-
Kaufmann, S.1
Schumacher, C.2
-
23
-
-
84928169488
-
-
(Version R package Version 4.6.0
-
Kelley K., (2019). MBESS: The MBESS R Package (Version R package Version 4.6.0). https://CRAN.R-project.org/package=MBESS
-
(2019)
MBESS: The MBESS R Package
-
-
Kelley, K.1
-
24
-
-
85011883610
-
The Bayesian new statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective
-
Kruschke J. K., Liddell T. M., (2018). The Bayesian new statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective. Psychonomic Bulletin & Review, 25(1), 178-206. https://doi.org/10.3758/s13423-016-1221-4
-
(2018)
Psychonomic Bulletin & Review
, vol.25
, Issue.1
, pp. 178-206
-
-
Kruschke, J.K.1
Liddell, T.M.2
-
25
-
-
2242448298
-
Bayesian selection on the number of factors in a factor analysis model
-
Lee S.-Y., Song X.-Y., (2002). Bayesian selection on the number of factors in a factor analysis model. Behaviormetrika, 29(1), 23-39. https://doi.org/10.2333/bhmk.29.23
-
(2002)
Behaviormetrika
, vol.29
, Issue.1
, pp. 23-39
-
-
Lee, S.-Y.1
Song, X.-Y.2
-
26
-
-
84855819431
-
Bayesian data-model fit assessment for structural equation modeling
-
Levy R., (2011). Bayesian data-model fit assessment for structural equation modeling. Structural Equation Modeling, 18(4), 663-685. https://doi.org/10.1080/10705511.2011.607723
-
(2011)
Structural Equation Modeling
, vol.18
, Issue.4
, pp. 663-685
-
-
Levy, R.1
-
28
-
-
85066988233
-
Determining the number of factors using parallel analysis and its recent variants
-
Lim S., Jahng S., (2019). Determining the number of factors using parallel analysis and its recent variants. Psychological Methods, 24(4), 452-467. https://doi.org/10.1037/met0000230
-
(2019)
Psychological Methods
, vol.24
, Issue.4
, pp. 452-467
-
-
Lim, S.1
Jahng, S.2
-
29
-
-
79961213152
-
MCMCpack: Markov chain Monte Carlo in R
-
Martin A. D., Quinn K. M., Park J. H., (2011). MCMCpack: Markov chain Monte Carlo in R. Journal of Statistical Software, 42(9), 1-21. https://doi.org/10.18637/jss.v042.i09
-
(2011)
Journal of Statistical Software
, vol.42
, Issue.9
, pp. 1-21
-
-
Martin, A.D.1
Quinn, K.M.2
Park, J.H.3
-
30
-
-
84873047637
-
Bayesian structural equation modeling: A more flexible representation of substantive theory
-
Muthén B., Asparouhov T., (2012). Bayesian structural equation modeling: A more flexible representation of substantive theory. Psychological Methods, 17(3), 313-335. https://doi.org/10.1037/a0026802
-
(2012)
Psychological Methods
, vol.17
, Issue.3
, pp. 313-335
-
-
Muthén, B.1
Asparouhov, T.2
-
31
-
-
0142168273
-
Repairing Tom Swift’s electric factor analysis machine
-
Preacher K. J., MacCallum R. C., (2003). Repairing Tom Swift’s electric factor analysis machine. Understanding Statistics, 2(1), 13-43. https://doi.org/10.1207/S15328031US0201_02
-
(2003)
Understanding Statistics
, vol.2
, Issue.1
, pp. 13-43
-
-
Preacher, K.J.1
MacCallum, R.C.2
-
33
-
-
84868253616
-
The rediscovery of bifactor measurement models
-
Reise S. P., (2012). The rediscovery of bifactor measurement models. Multivariate Behavioral Research, 47(5), 667-696. https://doi.org/10.1080/00273171.2012.715555
-
(2012)
Multivariate Behavioral Research
, vol.47
, Issue.5
, pp. 667-696
-
-
Reise, S.P.1
-
34
-
-
77956756020
-
Formal relations and an empirical comparison among the bi-factor, the testlet, and a second-order multidimensional IRT model
-
Rijmen F., (2010). Formal relations and an empirical comparison among the bi-factor, the testlet, and a second-order multidimensional IRT model. Journal of Educational Measurement, 47(3), 361-372. https://doi.org/10.1111/j.1745-3984.2010.00118.x
-
(2010)
Journal of Educational Measurement
, vol.47
, Issue.3
, pp. 361-372
-
-
Rijmen, F.1
-
35
-
-
85010666571
-
Fast Bayesian factor analysis via automatic rotations to sparsity
-
Ročková V., George E. I., (2016). Fast Bayesian factor analysis via automatic rotations to sparsity. Journal of the American Statistical Association, 111(516), 1608-1622. https://doi.org/10.1080/01621459.2015.1100620
-
(2016)
Journal of the American Statistical Association
, vol.111
, Issue.516
, pp. 1608-1622
-
-
Ročková, V.1
George, E.I.2
-
36
-
-
79958855301
-
Dimensionality assessment of ordered polytomous items with parallel analysis
-
Timmerman M. E., Lorenzo-Seva U., (2011). Dimensionality assessment of ordered polytomous items with parallel analysis. Psychological Methods, 16(2), 209-220. https://doi.org/10.1037/a0023353
-
(2011)
Psychological Methods
, vol.16
, Issue.2
, pp. 209-220
-
-
Timmerman, M.E.1
Lorenzo-Seva, U.2
-
37
-
-
0032363615
-
The effect of common variance and structure pattern on random data eigenvalues: Implications for the accuracy of parallel analysis
-
Turner N. E., (1998). The effect of common variance and structure pattern on random data eigenvalues: Implications for the accuracy of parallel analysis. Educational and Psychological Measurement, 58(4), 541-556. https://doi.org/10.1177/0013164498058004001
-
(1998)
Educational and Psychological Measurement
, vol.58
, Issue.4
, pp. 541-556
-
-
Turner, N.E.1
-
38
-
-
85043397425
-
Proportion of indicator common variance due to a factor as an effect size statistic in revised parallel analysis
-
Xia Y, Green S. B., Xu Y., Thompson M. S., (2018). Proportion of indicator common variance due to a factor as an effect size statistic in revised parallel analysis. Educational and Psychological Measurement, 79(1), 85-107. https://doi.org/10.1177/0013164418754611
-
(2018)
Educational and Psychological Measurement
, vol.79
, Issue.1
, pp. 85-107
-
-
Xia, Y.1
Green, S.B.2
Xu, Y.3
Thompson, M.S.4
-
39
-
-
58149371334
-
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(3), 432-442. https://doi.org/10.1037/0033-2909.99.3.432
-
(1986)
Psychological Bulletin
, vol.99
, Issue.3
, pp. 432-442
-
-
Zwick, W.R.1
Velicer, W.F.2
|