메뉴 건너뛰기




Volumn 53, Issue 2, 2011, Pages 308-331

Comparison of procedures to assess non-linear and time-varying effects in multivariable models for survival data

Author keywords

Comparison of approaches; Extended Cox model; Non linear effects; Survival analysis; Time varying effects

Indexed keywords

HAZARDS;

EID: 79952225145     PISSN: 03233847     EISSN: 15214036     Source Type: Journal    
DOI: 10.1002/bimj.201000159     Document Type: Article
Times cited : (28)

References (60)
  • 1
    • 0030327571 scopus 로고    scopus 로고
    • Time-dependent hazard ratio: modeling and hypothesis testing with application in lupus nephritis
    • Abrahamowicz, M., MacKenzie, T. and Esdaile, J. M. (1996). Time-dependent hazard ratio: modeling and hypothesis testing with application in lupus nephritis. Journal of the American Statistical Association 91, 1432-1439.
    • (1996) Journal of the American Statistical Association , vol.91 , pp. 1432-1439
    • Abrahamowicz, M.1    Mackenzie, T.2    Esdaile, J.M.3
  • 2
    • 33846202085 scopus 로고    scopus 로고
    • Joint estimation of time-dependent and non-linear effects of continuous covariates on survival
    • Abrahamowicz, M. and MacKenzie, T. A. (2007). Joint estimation of time-dependent and non-linear effects of continuous covariates on survival. Statistics in Medicine 26, 392-408.
    • (2007) Statistics in Medicine , vol.26 , pp. 392-408
    • Abrahamowicz, M.1    Mackenzie, T.A.2
  • 3
    • 0002652128 scopus 로고
    • A two-step regression model for hazard functions
    • Anderson, J. A. and Senthilselvan, A. (1982). A two-step regression model for hazard functions. Applied Statistics 31, 44-51.
    • (1982) Applied Statistics , vol.31 , pp. 44-51
    • Anderson, J.A.1    Senthilselvan, A.2
  • 4
    • 85163250384 scopus 로고    scopus 로고
    • BayesX - software for Bayesian inference in structured additive regression models. Version 2.00.
    • Belitz, C., Brezger, A., Kneib, T. and Lang, S. (2009). BayesX - software for Bayesian inference in structured additive regression models. Version 2.00.
    • (2009)
    • Belitz, C.1    Brezger, A.2    Kneib, T.3    Lang, S.4
  • 5
    • 19944372078 scopus 로고    scopus 로고
    • Generating survival times to simulate Cox proportional hazards models
    • Bender, R., Augustin, T. and Blettner, M. (2005). Generating survival times to simulate Cox proportional hazards models. Statistics in Medicine 24, 1713-1723.
    • (2005) Statistics in Medicine , vol.24 , pp. 1713-1723
    • Bender, R.1    Augustin, T.2    Blettner, M.3
  • 6
    • 0037446009 scopus 로고    scopus 로고
    • Dynamic Cox modelling based on fractional polynomials: time-variations in gastric cancer prognosis
    • Berger, U., Schäfer, J. and Ulm, K. (2003). Dynamic Cox modelling based on fractional polynomials: time-variations in gastric cancer prognosis. Statistics in Medicine 22, 1163-1180.
    • (2003) Statistics in Medicine , vol.22 , pp. 1163-1180
    • Berger, U.1    Schäfer, J.2    Ulm, K.3
  • 7
    • 0031921607 scopus 로고    scopus 로고
    • Feed forward neural networks for the analysis of censored survival data: a partial logistic regression approach
    • Biganzoli, E., Boracchi, P., Mariani, L. and Marubini, E. (1998). Feed forward neural networks for the analysis of censored survival data: a partial logistic regression approach. Statistics in Medicine 17, 1169-1186.
    • (1998) Statistics in Medicine , vol.17 , pp. 1169-1186
    • Biganzoli, E.1    Boracchi, P.2    Mariani, L.3    Marubini, E.4
  • 8
    • 34547297105 scopus 로고    scopus 로고
    • A partial likelihood approach to smooth estimation of dynamic covariate effects using penalised splines
    • Brown, D., Kauermann, G. and Ford, I. (2007). A partial likelihood approach to smooth estimation of dynamic covariate effects using penalised splines. Biometrical Journal 49, 1-12.
    • (2007) Biometrical Journal , vol.49 , pp. 1-12
    • Brown, D.1    Kauermann, G.2    Ford, I.3
  • 9
    • 85163242417 scopus 로고    scopus 로고
    • Assessment of time-varying long-term effects of therapies and prognostic factors. Ph.D. Thesis, Technische Universität Dortmund.
    • Buchholz, A. (2010). Assessment of time-varying long-term effects of therapies and prognostic factors. Ph.D. Thesis, Technische Universität Dortmund.
    • (2010)
    • Buchholz, A.1
  • 10
    • 85163243074 scopus 로고    scopus 로고
    • Modelling time-varying effects in large survival data sets may require categorisation of time: Does it influence the results of the MFPT approach? Submitted.
    • Buchholz, A., Sauerbrei, W. and Royston, P. (2010). Modelling time-varying effects in large survival data sets may require categorisation of time: Does it influence the results of the MFPT approach? Submitted.
    • (2010)
    • Buchholz, A.1    Sauerbrei, W.2    Royston, P.3
  • 11
    • 0038784393 scopus 로고    scopus 로고
    • Local linear estimation for time-dependent coefficients in Cox's regression model
    • Cai, Z. and Sun, Y. (2003). Local linear estimation for time-dependent coefficients in Cox's regression model. Scandinavian Journal of Statistics 30, 93-111.
    • (2003) Scandinavian Journal of Statistics , vol.30 , pp. 93-111
    • Cai, Z.1    Sun, Y.2
  • 14
    • 56349121502 scopus 로고    scopus 로고
    • Parametrization and penalties in spline models with an application to survival analysis
    • Costa, M. and Shaw, J. (2009). Parametrization and penalties in spline models with an application to survival analysis. Computational Statistics and Data Analysis 53, 657-670.
    • (2009) Computational Statistics and Data Analysis , vol.53 , pp. 657-670
    • Costa, M.1    Shaw, J.2
  • 17
    • 84950461478 scopus 로고
    • Estimating the error rate of a prediction rule: improvement on cross-validation
    • Efron, B. (1983). Estimating the error rate of a prediction rule: improvement on cross-validation. Journal of the American Statistical Association 78, 316-330.
    • (1983) Journal of the American Statistical Association , vol.78 , pp. 316-330
    • Efron, B.1
  • 20
    • 34547892291 scopus 로고    scopus 로고
    • Efron-type measures of prediction error for survival analysis
    • Gerds, T. A. and Schumacher, M. (2007). Efron-type measures of prediction error for survival analysis. Biometrics 63, 1283-1287.
    • (2007) Biometrics , vol.63 , pp. 1283-1287
    • Gerds, T.A.1    Schumacher, M.2
  • 21
    • 0003000728 scopus 로고
    • Regression models and non-proportional hazards in the analysis of breast cancer survival
    • Gore, S. M., Pocock, S. J. and Kerr, G. R. (1984). Regression models and non-proportional hazards in the analysis of breast cancer survival. Journal of the Royal Statistical Society, Series C 33, 176-195.
    • (1984) Journal of the Royal Statistical Society, Series C , vol.33 , pp. 176-195
    • Gore, S.M.1    Pocock, S.J.2    Kerr, G.R.3
  • 22
    • 21144472187 scopus 로고
    • Flexible methods for analyzing survival data using splines, with application to breast cancer prognosis
    • Gray, R. J. (1992). Flexible methods for analyzing survival data using splines, with application to breast cancer prognosis. Journal of the American Statistical Association 87, 942-951.
    • (1992) Journal of the American Statistical Association , vol.87 , pp. 942-951
    • Gray, R.J.1
  • 23
    • 0035530907 scopus 로고    scopus 로고
    • Measuring diagnostic accuracy of statistical prediction rules
    • Hand, D. (2001). Measuring diagnostic accuracy of statistical prediction rules. Statistica Neerlandica 55, 3-16.
    • (2001) Statistica Neerlandica , vol.55 , pp. 3-16
    • Hand, D.1
  • 24
    • 45849132989 scopus 로고    scopus 로고
    • The separation of timescales in Bayesian survival of the time-varying effect of a time-dependent exposure
    • Haneuse, S. J.-P., Rudser, K. D. and Gillen, D. L. (2008). The separation of timescales in Bayesian survival of the time-varying effect of a time-dependent exposure. Biostatistics 9, 400-410.
    • (2008) Biostatistics , vol.9 , pp. 400-410
    • Haneuse, S.J.-P.1    Rudser, K.D.2    Gillen, D.L.3
  • 26
    • 74749104118 scopus 로고    scopus 로고
    • Application of the Bayesian dynamic survival model in medicine
    • He, J., McGee, D. L. and Niu, X. (2010). Application of the Bayesian dynamic survival model in medicine. Statistics in Medicine 29, 347-360.
    • (2010) Statistics in Medicine , vol.29 , pp. 347-360
    • He, J.1    Mcgee, D.L.2    Niu, X.3
  • 27
    • 0031281322 scopus 로고    scopus 로고
    • Gaining more flexibility in Cox proportional hazards regression models with cubic spline functions
    • Heinzl, H. and Kaider, A. (1997). Gaining more flexibility in Cox proportional hazards regression models with cubic spline functions. Computer Methods and Programs in Biomedicine 54, 201-208.
    • (1997) Computer Methods and Programs in Biomedicine , vol.54 , pp. 201-208
    • Heinzl, H.1    Kaider, A.2
  • 29
    • 0028362674 scopus 로고
    • Assessing time-by-covariate interactions in proportional hazards regression models using cubic spline functions
    • Hess, K. R. (1994). Assessing time-by-covariate interactions in proportional hazards regression models using cubic spline functions. Statistics in Medicine 13, 1045-1062.
    • (1994) Statistics in Medicine , vol.13 , pp. 1045-1062
    • Hess, K.R.1
  • 31
    • 78651380685 scopus 로고    scopus 로고
    • Building Cox-type structured hazard regression models with time-varying effects
    • Hofner, B., Kneib, T., Hartl, W. and Küchenhoff, H. (2011). Building Cox-type structured hazard regression models with time-varying effects. Statistical Modelling 11, 3-24.
    • (2011) Statistical Modelling , vol.11 , pp. 3-24
    • Hofner, B.1    Kneib, T.2    Hartl, W.3    Küchenhoff, H.4
  • 32
    • 0031014355 scopus 로고    scopus 로고
    • The role of frailty models and accelerated failure time models in describing heterogeneity due to omitted covariates
    • Keiding, N., Andersen, P. K. and Klein, J. P. (1997). The role of frailty models and accelerated failure time models in describing heterogeneity due to omitted covariates. Statistics in Medicine 16, 215-224.
    • (1997) Statistics in Medicine , vol.16 , pp. 215-224
    • Keiding, N.1    Andersen, P.K.2    Klein, J.P.3
  • 33
    • 33847380991 scopus 로고    scopus 로고
    • A mixed model approach for geoadditive hazard regression
    • Kneib, T. and Fahrmeir, L. (2007). A mixed model approach for geoadditive hazard regression. Scandinavian Journal of Statistics 34, 207-228.
    • (2007) Scandinavian Journal of Statistics , vol.34 , pp. 207-228
    • Kneib, T.1    Fahrmeir, L.2
  • 35
    • 0043146736 scopus 로고    scopus 로고
    • S-Plus Professional Version 4.5
    • MathSoft. Mathsoft, Inc., Seattle, WA.
    • MathSoft. (1998). S-Plus Professional Version 4.5. Mathsoft, Inc., Seattle, WA.
    • (1998)
  • 36
    • 0033638572 scopus 로고    scopus 로고
    • Bayesian estimators for conditional hazard functions
    • McKeague, I. W. and Tighiouart, M. (2000). Bayesian estimators for conditional hazard functions. Biometrics 56, 1007-1015.
    • (2000) Biometrics , vol.56 , pp. 1007-1015
    • Mckeague, I.W.1    Tighiouart, M.2
  • 37
    • 0022245463 scopus 로고
    • A global goodness-of-fit statistic for the proportional hazards model
    • Moreau, T., O'Quigley, J. and Mesbah, M. (1985). A global goodness-of-fit statistic for the proportional hazards model. Applied Statistics 34, 212-218.
    • (1985) Applied Statistics , vol.34 , pp. 212-218
    • Moreau, T.1    O'Quigley, J.2    Mesbah, M.3
  • 38
    • 0030979983 scopus 로고    scopus 로고
    • An empirical comparison of statistical tests for assessing the proportional hazards assumption of Cox's model
    • Ng'Andu, N. H. (1997). An empirical comparison of statistical tests for assessing the proportional hazards assumption of Cox's model. Statistics in Medicine 16, 611-626.
    • (1997) Statistics in Medicine , vol.16 , pp. 611-626
    • Ng'Andu, N.H.1
  • 39
    • 0025774226 scopus 로고
    • The problem of a covariate-time qualitative interaction in a survival study
    • O'Quigley, J. and Pessione, F. (1991). The problem of a covariate-time qualitative interaction in a survival study. Biometrics 47, 101-115.
    • (1991) Biometrics , vol.47 , pp. 101-115
    • O'Quigley, J.1    Pessione, F.2
  • 40
    • 85163247191 scopus 로고    scopus 로고
    • coxvc: Cox models with time varying effects of the covariates and reduced rank models. R package version 1-1-1.
    • Perperoglou, A. (2005). coxvc: Cox models with time varying effects of the covariates and reduced rank models. R package version 1-1-1.
    • (2005)
    • Perperoglou, A.1
  • 42
    • 33746873296 scopus 로고    scopus 로고
    • Reduced-rank hazard regression for modelling non-proportional hazards
    • Perperoglou, A., le Cessie, S. and van Houwelingen, H. C. (2006b). Reduced-rank hazard regression for modelling non-proportional hazards. Statistics in Medicine 25, 2831-2845.
    • (2006) Statistics in Medicine , vol.25 , pp. 2831-2845
    • Perperoglou, A.1    le Cessie, S.2    van Houwelingen, H.C.3
  • 43
    • 84863304598 scopus 로고    scopus 로고
    • R: A Language and Environment for Statistical Computing
    • R Development Core Team R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0.
    • R Development Core Team (2009). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0.
    • (2009)
  • 44
    • 0004509186 scopus 로고
    • Regression using fractional polynomials of continuous covariates: parsimonious parametric modelling
    • Royston, P. and Altman, D. G. (1994). Regression using fractional polynomials of continuous covariates: parsimonious parametric modelling. Applied Statistics 43, 429-453.
    • (1994) Applied Statistics , vol.43 , pp. 429-453
    • Royston, P.1    Altman, D.G.2
  • 45
    • 0037470273 scopus 로고    scopus 로고
    • Stability of multivariable fractional polynomial models with selection of variables and transformations: a bootstrap investigation
    • Royston, P. and Sauerbrei, W. (2003). Stability of multivariable fractional polynomial models with selection of variables and transformations: a bootstrap investigation. Statistics in Medicine 22, 639-659.
    • (2003) Statistics in Medicine , vol.22 , pp. 639-659
    • Royston, P.1    Sauerbrei, W.2
  • 46
    • 84948184622 scopus 로고    scopus 로고
    • Multivariable Model-building: A Pragmatic Approach to Regression Analysis Based on Fractional Polynomials for Modelling Continuous Variables
    • Wiley, Chichester.
    • Royston, P. and Sauerbrei, W. (2008). Multivariable Model-building: A Pragmatic Approach to Regression Analysis Based on Fractional Polynomials for Modelling Continuous Variables. Wiley, Chichester.
    • (2008)
    • Royston, P.1    Sauerbrei, W.2
  • 47
    • 79958233615 scopus 로고    scopus 로고
    • Bayesian fractional polynomials
    • to appear. DOI: 10.1007/s11222-010-9170-7.
    • Sabanés Bové, D. and Held, L. (2010). Bayesian fractional polynomials. Statistics and Computing, to appear. DOI: 10.1007/s11222-010-9170-7.
    • (2010) Statistics and Computing
    • Sabanés Bové, D.1    Held, L.2
  • 48
    • 3843060004 scopus 로고    scopus 로고
    • Martingale difference residuals as a diagnostic tool for the Cox model
    • Sasieni, P. D. and Winnett, A. (2003). Martingale difference residuals as a diagnostic tool for the Cox model. Biometrika 90, 899-912.
    • (2003) Biometrika , vol.90 , pp. 899-912
    • Sasieni, P.D.1    Winnett, A.2
  • 49
    • 0033474286 scopus 로고    scopus 로고
    • Building multivariable prognostic and diagnostic models: transformation of the predictors by using fractional polynomials
    • Sauerbrei, W. and Royston, P. (1999). Building multivariable prognostic and diagnostic models: transformation of the predictors by using fractional polynomials. Journal of the Royal Statistical Society, Series A 162, 71-94.
    • (1999) Journal of the Royal Statistical Society, Series A , vol.162 , pp. 71-94
    • Sauerbrei, W.1    Royston, P.2
  • 50
    • 38849176100 scopus 로고    scopus 로고
    • Selection of important variables and determination of functional form for continuous predictors in multivariable model building
    • Sauerbrei, W., Royston, P. and Binder, H. (2007a). Selection of important variables and determination of functional form for continuous predictors in multivariable model building. Statistics in Medicine 26, 5512-5528.
    • (2007) Statistics in Medicine , vol.26 , pp. 5512-5528
    • Sauerbrei, W.1    Royston, P.2    Binder, H.3
  • 51
    • 34547248336 scopus 로고    scopus 로고
    • A new proposal for multivariable modelling of time-varying effects in survival data based on fractional polynomial time-transformation
    • Sauerbrei, W., Royston, P. and Look, M. (2007b). A new proposal for multivariable modelling of time-varying effects in survival data based on fractional polynomial time-transformation. Biometrical Journal 49, 453-473.
    • (2007) Biometrical Journal , vol.49 , pp. 453-473
    • Sauerbrei, W.1    Royston, P.2    Look, M.3
  • 52
    • 85163245666 scopus 로고    scopus 로고
    • Timereg: timereg package for flexible regression models for survival data. R package version 1.2-4.
    • Scheike, T. (2009). Timereg: timereg package for flexible regression models for survival data. R package version 1.2-4.
    • (2009)
    • Scheike, T.1
  • 53
    • 1542321017 scopus 로고    scopus 로고
    • On estimation and tests of time-varying effects in the proportional hazards model
    • Scheike, T. H. and Martinussen, T. (2004). On estimation and tests of time-varying effects in the proportional hazards model. Scandinavian Journal of Statistics 31, 51-62.
    • (2004) Scandinavian Journal of Statistics , vol.31 , pp. 51-62
    • Scheike, T.H.1    Martinussen, T.2
  • 54
    • 69949088278 scopus 로고    scopus 로고
    • The estimation of average hazard ratios by weighted Cox regression
    • Schemper, M., Wakounig, S. and Heinze, G. (2009). The estimation of average hazard ratios by weighted Cox regression. Statistics in Medicine 28, 2473-2489.
    • (2009) Statistics in Medicine , vol.28 , pp. 2473-2489
    • Schemper, M.1    Wakounig, S.2    Heinze, G.3
  • 55
    • 0030045447 scopus 로고    scopus 로고
    • Randomized and non-randomized patients in clinical trials: experiences with comprehensive cohort studies
    • Schmoor, C., Olschewski, M. and Schumacher, M. (1996). Randomized and non-randomized patients in clinical trials: experiences with comprehensive cohort studies. Statistics in Medicine 15, 263-271.
    • (1996) Statistics in Medicine , vol.15 , pp. 263-271
    • Schmoor, C.1    Olschewski, M.2    Schumacher, M.3
  • 56
    • 0003393711 scopus 로고    scopus 로고
    • Stata Statistical Software: Release 10
    • StataCorp StataCorp LP, College Station, TX.
    • StataCorp (2007). Stata Statistical Software: Release 10. StataCorp LP, College Station, TX.
    • (2007)
  • 57
    • 0003570192 scopus 로고    scopus 로고
    • Modeling Survival Data: Extending the Cox Model
    • Springer, New York.
    • Therneau, T. M. and Grambsch, P. M. (2000). Modeling Survival Data: Extending the Cox Model. Springer, New York.
    • (2000)
    • Therneau, T.M.1    Grambsch, P.M.2
  • 59
    • 0033616909 scopus 로고    scopus 로고
    • Multiple imputation of missing blood pressure covariates in survival analysis
    • van Buuren, S., Boshuizen, H. and Knook, D. (1999). Multiple imputation of missing blood pressure covariates in survival analysis. Statistics in Medicine 18, 681-694.
    • (1999) Statistics in Medicine , vol.18 , pp. 681-694
    • van Buuren, S.1    Boshuizen, H.2    Knook, D.3
  • 60
    • 0029586866 scopus 로고
    • Time-dependent effects of fixed covariates in Cox regression
    • Verweij, P. J. M. and van Houwelingen, H. C. (1995). Time-dependent effects of fixed covariates in Cox regression. Biometrics 51, 1550-1556.
    • (1995) Biometrics , vol.51 , pp. 1550-1556
    • Verweij, P.J.M.1    van Houwelingen, H.C.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.