References
- Hogarty KY, Kromrey JD, Ferron JM, et al. Selection of variables in exploratory factor analysis: an empirical comparison of a stepwise and traditional approach. Psychometrika. 2004;69(4):593–611. doi: 10.1007/BF02289857
- Kano Y, Ihara M. Identification of inconsistent variates in factor analysis. Psychometrika. 1994;59:5–20. doi: 10.1007/BF02294262
- Hirose K, Konishi S. Variable selection via the weighted group lasso for factor analysis models. Canad J Stat. 2012;40(2):345–361. doi: 10.1002/cjs.11129
- Choi J, Zou H, Oehlert G. A penalized maximum likelihood approach to sparse factor analysis. Stat Interface. 2011;3(4):429–436. doi: 10.4310/SII.2010.v3.n4.a1
- Ning L, Georgiou TT. Sparse factor analysis via likelihood and l1 regularization. Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, Orlando; 2011.
- Hirose K, Yamamoto M. Sparse estimation via nonconcave penalized likelihood in factor analysis model. J Stat Comput. 2015;25:863–875. doi: 10.1007/s11222-014-9458-0
- Fan J, Li R. Variable selection via nonconcave penalized likelihood and its oracle properties. J Am Stat Assoc. 2001;96:1348–1360. doi: 10.1198/016214501753382273
- Zhang C. Nearly unbiased variable selection under minimax concave penalty. Ann Stat. 2010;38:894–942. doi: 10.1214/09-AOS729
- Huang J, Breheny P, Ma S. A selective review of group selection in high-dimensional models. Stat Sci. 2012;27(4):481–499. doi: 10.1214/12-STS392
- Simon N, Friedman J, Hastie T, et al. A sparse-group lasso. J Comput Graph Stat. 2013;22(2):231–245. doi: 10.1080/10618600.2012.681250
- Meier L, van de Geer S, Bhlmann P. The grouped lasso for logistic regression. J R Statist Soc Ser B. 2008;70(1):53–71. doi: 10.1111/j.1467-9868.2007.00627.x
- Vincent M, Hansen NR. Sparse group lasso and high dimensional multinomial classiffication. Comput Stat Data Anal. 2013;71:771–786. doi: 10.1016/j.csda.2013.06.004
- Wang Q, Zhao D. Penalization with group-wise sparsity: econometric applications to ebay motors online auctions. Empir Econ. 2018: 1–22. doi: 10.1007/s00181-018-1460-5
- Hoerl AE, Kennard RW. Ridge regression: biased estimation for nonorthogonal problems. Technometrics. 1970;12(1):55–67. doi: 10.1080/00401706.1970.10488634
- Tibshirani R. Regression shrinkage and selection via the lasso. J R Statist Soc Ser B. 1996;58(1):267–288.
- Tibshirani R. The lasso method for variable selection in the Cox model. Stat Med. 1997;16:385–395. doi: 10.1002/(SICI)1097-0258(19970228)16:4<385::AID-SIM380>3.0.CO;2-3
- Lokhorst J. The lasso and generalized linear models. Technical report, University of Adelaide, 1999.
- Roth V. The generalized lasso. IEEE Trans Neural Netw. 2004;15(1):16–28. doi: 10.1109/TNN.2003.809398
- Zou H, Hastie T. Regularization and variable selection via the elastic net. J R Statist Soc Ser B. 2005;67(2):301–320. doi: 10.1111/j.1467-9868.2005.00503.x
- Yuan M, Lin Y. Model selection and estimation in regression with grouped variables. J R Statist Soc Ser B. 2006;68(1):49–67. doi: 10.1111/j.1467-9868.2005.00532.x
- Hirose K, Yamamoto M. Estimation of an oblique structure via penalized likelihood factor analysis. Comput Stat Data Anal. 2014;79:120–132. doi: 10.1016/j.csda.2014.05.011
- Stock JH, Watson MW. Forecasting using principal components from a large number of predictors. J Amer Statist Assoc. 2002;97(460):1167–1179. doi: 10.1198/016214502388618960
- Lawley DN, Maxwell AE. Factor analysis as a statistical method. 2nd ed. London: Butterworths; 1971.
- Ray S, Lindsay BG. Model selection in high dimensions: a quadratic-risk based approach. J R Statist Soc Ser B. 2008;70(1):95–118.
- Wang Q, Lindsay BG. Variance estimation of a general U-statistic with application to cross-validation. Stat Sin. 2014;24(3):1171–1141.
- Wang Q. Investigation of topics in U-statistics and their applications in risk estimation and cross-validation [PhD thesis]. The Pennsylvania State University; 2012.
- Schwarz G. Estimating the dimension of a model. Ann Stat. 1978;6(2):461–464. doi: 10.1214/aos/1176344136
- Akaike H. A new look at the statistical model identification. IEEE Trans Automat Contr. 1974;19(6):716–723. doi: 10.1109/TAC.1974.1100705
- Lopes HF, West M. Bayesian model assessment in factor analysis. Stat Sin. 2004;14:41–67.
- Revelle W, Wilt J, Rosenthal A. Individual differences in cognition: new methods for examining the personality cognition link. New York: Springer; 2010.
- Condon D, Revelle W. The international cognitive ability resource: development and initial validation of a public-domain measure. Intelligence. 2014;43:52–64. doi: 10.1016/j.intell.2014.01.004
- Revelle W. psych: procedures for psychological, psychometric, and personality research. Technical report, 2017.
- Abdi H. Factor rotations in factor analyses. In: Lewis-Beck M, Bryman A, Futing T, editors. Encyclopedia of social sciences research methods. Thousand Oaks (CA): Sage; 2003. p. 978–982.
- Kenny DA. Multiple latent variable models: confirmatory factor analysis. 2016.