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Volumn 60, Issue 3, 2011, Pages 377-395

Selection of ordinally scaled independent variables with applications to international classification of functioning core sets

Author keywords

Boosting; Group lasso; International classification of functioning core sets; Ordinal predictors; Ridge regression; Variable selection

Indexed keywords


EID: 79954618626     PISSN: 00359254     EISSN: 14679876     Source Type: Journal    
DOI: 10.1111/j.1467-9876.2010.00753.x     Document Type: Article
Times cited : (29)

References (51)
  • 1
    • 0034872552 scopus 로고    scopus 로고
    • Sequential ordinal modeling with applications to survival data
    • Albert, J. H. and Chib, S. (2001) Sequential ordinal modeling with applications to survival data. Biometrics, 57, 829-836.
    • (2001) Biometrics , vol.57 , pp. 829-836
    • Albert, J.H.1    Chib, S.2
  • 2
    • 0024586199 scopus 로고
    • Ordinal regression models for epidemiologic data
    • Armstrong, B. and Sloan, M. (1989) Ordinal regression models for epidemiologic data. Am. J. Epidem., 129, 191-204.
    • (1989) Am. J. Epidem. , vol.129 , pp. 191-204
    • Armstrong, B.1    Sloan, M.2
  • 3
    • 0000203627 scopus 로고
    • Additive isotonic models
    • Bacchetti, P. (1989) Additive isotonic models. J. Am. Statist. Ass., 84, 289-294.
    • (1989) J. Am. Statist. Ass. , vol.84 , pp. 289-294
    • Bacchetti, P.1
  • 5
    • 0346786584 scopus 로고    scopus 로고
    • Arcing classifiers
    • Breiman, L. (1998) Arcing classifiers. Ann. Statist., 26, 801-849.
    • (1998) Ann. Statist. , vol.26 , pp. 801-849
    • Breiman, L.1
  • 6
    • 0000275022 scopus 로고    scopus 로고
    • Prediction games and arcing algorithms
    • Breiman, L. (1999) Prediction games and arcing algorithms. Neur. Computn, 11, 1493-1517.
    • (1999) Neur. Computn , vol.11 , pp. 1493-1517
    • Breiman, L.1
  • 7
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • Breiman, L. (2001) Random forests. Mach. Learn., 45, 5-32.
    • (2001) Mach. Learn. , vol.45 , pp. 5-32
    • Breiman, L.1
  • 8
    • 33745157294 scopus 로고    scopus 로고
    • Boosting for high-dimensional linear models
    • Bühlmann, P. (2006) Boosting for high-dimensional linear models. Ann. Statist., 34, 559-583.
    • (2006) Ann. Statist. , vol.34 , pp. 559-583
    • Bühlmann, P.1
  • 9
    • 41549141939 scopus 로고    scopus 로고
    • Boosting algorithms: regularization prediction and model fitting
    • Bühlmann, P. and Hothorn, T. (2007) Boosting algorithms: regularization prediction and model fitting. Statist. Sci., 22, 477-505.
    • (2007) Statist. Sci. , vol.22 , pp. 477-505
    • Bühlmann, P.1    Hothorn, T.2
  • 10
    • 0043245810 scopus 로고    scopus 로고
    • Boosting with the L2 loss: regression and classification
    • Bühlmann, P. and Yu, B. (2003) Boosting with the L2 loss: regression and classification. J. Am. Statist. Ass., 98, 324-339.
    • (2003) J. Am. Statist. Ass. , vol.98 , pp. 324-339
    • Bühlmann, P.1    Yu, B.2
  • 14
    • 0029021856 scopus 로고
    • Location-scale cumulative odds models for ordinal data: a generalized non-linear model approach
    • Cox, C. (1995) Location-scale cumulative odds models for ordinal data: a generalized non-linear model approach. Statist. Med., 14, 1191-1203.
    • (1995) Statist. Med. , vol.14 , pp. 1191-1203
    • Cox, C.1
  • 15
    • 1542784498 scopus 로고    scopus 로고
    • Variable selection via nonconcave penalized likelihood and its oracle properties
    • Fan, J. and Li, R. (2001) Variable selection via nonconcave penalized likelihood and its oracle properties. J. Am. Statist. Ass., 96, 1348-1360.
    • (2001) J. Am. Statist. Ass. , vol.96 , pp. 1348-1360
    • Fan, J.1    Li, R.2
  • 16
    • 0002978642 scopus 로고    scopus 로고
    • Experiments with a new boosting algorithm
    • In - San Francisco: Morgan Kaufmann.
    • Freund, Y. and Schapire, R. E. (1996) Experiments with a new boosting algorithm. In Proc. 13th Int. Conf. Machine Learning, pp. 148-156. San Francisco: Morgan Kaufmann.
    • (1996) Proc. 13th Int. Conf. Machine Learning , pp. 148-156
    • Freund, Y.1    Schapire, R.E.2
  • 17
    • 0034164230 scopus 로고    scopus 로고
    • Additive logistic regression: a statistical view of boosting
    • Friedman, J. H., Hastie, T. and Tibshirani, R. (2000) Additive logistic regression: a statistical view of boosting. Ann. Statist., 28, 337-407.
    • (2000) Ann. Statist. , vol.28 , pp. 337-407
    • Friedman, J.H.1    Hastie, T.2    Tibshirani, R.3
  • 18
    • 77349114693 scopus 로고    scopus 로고
    • Penalized regression with ordinal predictors
    • Gertheiss, J. and Tutz, G. (2009) Penalized regression with ordinal predictors. Int. Statist. Rev., 77, 345-365.
    • (2009) Int. Statist. Rev. , vol.77 , pp. 345-365
    • Gertheiss, J.1    Tutz, G.2
  • 19
    • 84859813876 scopus 로고    scopus 로고
    • Sparse modeling of categorial explanatory variables
    • to be published
    • Gertheiss, J. and Tutz, G. (2010) Sparse modeling of categorial explanatory variables. Ann. Appl. Statist., to be published,.
    • (2010) Ann. Appl. Statist.
    • Gertheiss, J.1    Tutz, G.2
  • 24
    • 33749677657 scopus 로고    scopus 로고
    • Unbiased recursive partitioning: a conditional inference framework
    • Hothorn, T., Hornik, K. and Zeileis, A. (2006) Unbiased recursive partitioning: a conditional inference framework. J. Computnl Graph. Statist., 15, 651-674.
    • (2006) J. Computnl Graph. Statist. , vol.15 , pp. 651-674
    • Hothorn, T.1    Hornik, K.2    Zeileis, A.3
  • 25
    • 0001354983 scopus 로고    scopus 로고
    • Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion
    • Hurvich, C. M., Simonoff, J. S. and Tsai, C.-L. (1998) Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion. J. R. Statist. Soc. B, 60, 271-293.
    • (1998) J. R. Statist. Soc. B , vol.60 , pp. 271-293
    • Hurvich, C.M.1    Simonoff, J.S.2    Tsai, C.-L.3
  • 27
    • 0035285349 scopus 로고    scopus 로고
    • Analyzing incomplete political science data: an alternative algorithm for multiple imputation
    • King, G., Honaker, J., Joseph, A. and Scheve, K. (2001) Analyzing incomplete political science data: an alternative algorithm for multiple imputation. Am. Polit. Sci. Rev., 95, 49-69.
    • (2001) Am. Polit. Sci. Rev. , vol.95 , pp. 49-69
    • King, G.1    Honaker, J.2    Joseph, A.3    Scheve, K.4
  • 28
    • 34648835120 scopus 로고    scopus 로고
    • Generalized monotonic regression based on B-splines with an application to air pollution data
    • Leitenstorfer, F. and Tutz, G. (2007) Generalized monotonic regression based on B-splines with an application to air pollution data. Biostatistics, 8, 654-673.
    • (2007) Biostatistics , vol.8 , pp. 654-673
    • Leitenstorfer, F.1    Tutz, G.2
  • 29
    • 22544479106 scopus 로고    scopus 로고
    • The analysis of ordinal categorical data: an overview and a survey of recent developments
    • Liu, Q. and Agresti, A. (2005) The analysis of ordinal categorical data: an overview and a survey of recent developments. Test, 14, 1-73.
    • (2005) Test , vol.14 , pp. 1-73
    • Liu, Q.1    Agresti, A.2
  • 30
    • 37249033229 scopus 로고    scopus 로고
    • Group additive regression models for genomic data analysis
    • Luan, Y. and Li, H. (2008) Group additive regression models for genomic data analysis. Biostatistics, 9, 100-113.
    • (2008) Biostatistics , vol.9 , pp. 100-113
    • Luan, Y.1    Li, H.2
  • 31
    • 0001306637 scopus 로고
    • Regression models for ordinal data (with discussion)
    • McCullagh, P. (1980) Regression models for ordinal data (with discussion). J. R. Statist. Soc. B, 42, 109-142.
    • (1980) J. R. Statist. Soc. B , vol.42 , pp. 109-142
    • McCullagh, P.1
  • 32
    • 0027569430 scopus 로고
    • The MOS 36-item short-form health survey (SF-36): II, psychometric and clinical tests of validity in measuring physical and mental health constructs
    • McHorney, C. A., Ware, J. E. and Raczek, A. E. (1993) The MOS 36-item short-form health survey (SF-36): II, psychometric and clinical tests of validity in measuring physical and mental health constructs. Med. Care, 31, 247-263.
    • (1993) Med. Care , vol.31 , pp. 247-263
    • McHorney, C.A.1    Ware, J.E.2    Raczek, A.E.3
  • 34
    • 0001395585 scopus 로고
    • Partial proportional odds models for ordinal response variables
    • Peterson, B. and Harrell, F. E. (1990) Partial proportional odds models for ordinal response variables. Appl. Statist., 39, 205-217.
    • (1990) Appl. Statist. , vol.39 , pp. 205-217
    • Peterson, B.1    Harrell, F.E.2
  • 35
    • 70149113077 scopus 로고    scopus 로고
    • R Development Core Team Vienna: R Foundation for Statistical Computing.
    • R Development Core Team (2009) R: a Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing.
    • (2009) R: a Language and Environment for Statistical Computing
  • 36
    • 0025448521 scopus 로고
    • The strength of weak learnability
    • Schapire, R. E. (1990) The strength of weak learnability. Mach. Learn., 5, 197-227.
    • (1990) Mach. Learn. , vol.5 , pp. 197-227
    • Schapire, R.E.1
  • 37
    • 34548232392 scopus 로고    scopus 로고
    • Input selection and shrinkage in multiresponse linear regression. Computnl Statist
    • Similä, T. and Tikka, J. (2007) Input selection and shrinkage in multiresponse linear regression. Computnl Statist. Data Anal., 52, 406-422.
    • (2007) Data Anal. , vol.52 , pp. 406-422
    • Similä, T.1    Tikka, J.2
  • 38
    • 16644370969 scopus 로고    scopus 로고
    • Applying the ICF in medicine
    • Stucki, G. and Grimby, G. (2004) Applying the ICF in medicine. J. Rehabilitn Med., suppl., 44, 5-6.
    • (2004) J. Rehabilitn Med. , vol.44 , Issue.SUPPL. , pp. 5-6
    • Stucki, G.1    Grimby, G.2
  • 39
    • 0001287271 scopus 로고    scopus 로고
    • Regression shrinkage and selection via the lasso
    • Tibshirani, R. (1996) Regression shrinkage and selection via the lasso. J. R. Statist. Soc. B, 58, 267-288.
    • (1996) J. R. Statist. Soc. B , vol.58 , pp. 267-288
    • Tibshirani, R.1
  • 41
    • 84907506916 scopus 로고    scopus 로고
    • quadprog: functions to solve quadratic programming problems
    • Turlach, B. A. (2009) quadprog: functions to solve quadratic programming problems. R Package Version 1.4-12.
    • (2009) R Package Version 1.4-12
    • Turlach, B.A.1
  • 42
    • 33845509035 scopus 로고    scopus 로고
    • Generalized additive modeling with implicit variable selection by likelihood-based boosting
    • Tutz, G. and Binder, H. (2006) Generalized additive modeling with implicit variable selection by likelihood-based boosting. Biometrics, 62, 961-971.
    • (2006) Biometrics , vol.62 , pp. 961-971
    • Tutz, G.1    Binder, H.2
  • 43
    • 77749280569 scopus 로고    scopus 로고
    • Feature extraction in signal regression: a boosting technique for functional data regression
    • Tutz, G. and Gertheiss, J. (2010) Feature extraction in signal regression: a boosting technique for functional data regression. J. Computnl Graph. Statist., 19, 154-174.
    • (2010) J. Computnl Graph. Statist. , vol.19 , pp. 154-174
    • Tutz, G.1    Gertheiss, J.2
  • 45
    • 0023154433 scopus 로고
    • Coding ordinal independent variables in multiple regression analysis
    • Walter, S. D., Feinstein, A. R. and Wells, C. K. (1987) Coding ordinal independent variables in multiple regression analysis. Am. J. Epidem., 125, 319-323.
    • (1987) Am. J. Epidem. , vol.125 , pp. 319-323
    • Walter, S.D.1    Feinstein, A.R.2    Wells, C.K.3
  • 46
    • 47749144333 scopus 로고    scopus 로고
    • A note on adaptive group lasso
    • Wang, H. and Leng, C. (2008) A note on adaptive group lasso. Computnl Statist. Data Anal., 52, 5277-5286.
    • (2008) Computnl Statist. Data Anal. , vol.52 , pp. 5277-5286
    • Wang, H.1    Leng, C.2
  • 47
    • 0026877917 scopus 로고
    • The MOS 36-item short-form health survey (SF-36): I, conceptual framework and item selection
    • Ware, J. E. and Sherbourne, C. (1992) The MOS 36-item short-form health survey (SF-36): I, conceptual framework and item selection. Med. Care, 30, 473-483.
    • (1992) Med. Care , vol.30 , pp. 473-483
    • Ware, J.E.1    Sherbourne, C.2
  • 49
    • 49749148013 scopus 로고    scopus 로고
    • Variable selection in penalized model-based clustering via regularization on grouped parameters
    • Xie, B., Pan, W. and Shen, X. (2008) Variable selection in penalized model-based clustering via regularization on grouped parameters. Biometrics, 64, 921-930.
    • (2008) Biometrics , vol.64 , pp. 921-930
    • Xie, B.1    Pan, W.2    Shen, X.3
  • 50
    • 33645035051 scopus 로고    scopus 로고
    • Model selection and estimation in regression with grouped variables
    • Yuan, M. and Lin, Y. (2006) Model selection and estimation in regression with grouped variables. J. R. Statist. Soc. B, 68, 49-67.
    • (2006) J. R. Statist. Soc. B , vol.68 , pp. 49-67
    • Yuan, M.1    Lin, Y.2
  • 51
    • 16244401458 scopus 로고    scopus 로고
    • Regularization and variable selection via the elastic net
    • Zou, H. and Hastie, T. (2005) Regularization and variable selection via the elastic net. J. R. Statist. Soc. B, 67, 301-320.
    • (2005) J. R. Statist. Soc. B , vol.67 , pp. 301-320
    • Zou, H.1    Hastie, T.2


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