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Volumn 34, Issue 1, 2007, Pages 33-52

Choice between semi-parametric estimators of Markov and non-Markov multi-state models from coarsened observations

Author keywords

Counting processes; Cross validation; Dementia; Interval censoring; Kullback Leibler loss; Markov models; Multi state models; Penalized likelihood; Semi Markov models

Indexed keywords


EID: 33847411839     PISSN: 03036898     EISSN: 14679469     Source Type: Journal    
DOI: 10.1111/j.1467-9469.2006.00536.x     Document Type: Article
Times cited : (56)

References (34)
  • 1
    • 0000047140 scopus 로고
    • Nonparametric inference for a family of counting processes
    • Aalen, O. O. (1978). Nonparametric inference for a family of counting processes. Ann. Statist. 6, 701- 726.
    • (1978) Ann. Statist , vol.6 , pp. 701-726
    • Aalen, O.O.1
  • 2
    • 0001602163 scopus 로고
    • An empirical transition matrix for non-homogenous Markov chains based on censored observations
    • Aalen, O. O. & Johansen, S. (1978). An empirical transition matrix for non-homogenous Markov chains based on censored observations. Scand. J. Statist. 5, 141-150.
    • (1978) Scand. J. Statist , vol.5 , pp. 141-150
    • Aalen, O.O.1    Johansen, S.2
  • 3
    • 0035191590 scopus 로고    scopus 로고
    • Covariate adjustment of event histories estimated from Markov chains: The additive approach
    • Aalen, O. O., Borgan, Ø., & Fekjær, H. (2001). Covariate adjustment of event histories estimated from Markov chains: the additive approach. Biometrics 57, 993-1001.
    • (2001) Biometrics , vol.57 , pp. 993-1001
    • Aalen, O.O.1    Borgan, O.2    Fekjær, H.3
  • 5
    • 84925604888 scopus 로고    scopus 로고
    • No unbiased estimator of the variance of the K-fold cross-validation
    • Bengio, Y. & Grandvalet, Y. (2004). No unbiased estimator of the variance of the K-fold cross-validation. J. Mach. Learn. Res. 5, 1089-1105.
    • (2004) J. Mach. Learn. Res , vol.5 , pp. 1089-1105
    • Bengio, Y.1    Grandvalet, Y.2
  • 7
    • 34547288139 scopus 로고    scopus 로고
    • Likelihood for generally coarsened observations from multistate or counting process models
    • in press, doi: 10.1111/j.1467.9469.2006.00518
    • Commenges, D. & Gégout-Petit, A. (2006). Likelihood for generally coarsened observations from multistate or counting process models. Scand. J. Statist., in press, doi: 10.1111/j.1467.9469.2006.00518.
    • (2006) Scand. J. Statist
    • Commenges, D.1    Gégout-Petit, A.2
  • 8
    • 2342565104 scopus 로고    scopus 로고
    • Multi-state model for dementia, institutionalization and death
    • Commenges, D. & Joly, P. (2004). Multi-state model for dementia, institutionalization and death. Commun. Statist. A 33, 1315-1326.
    • (2004) Commun. Statist. A , vol.33 , pp. 1315-1326
    • Commenges, D.1    Joly, P.2
  • 9
    • 0347724079 scopus 로고    scopus 로고
    • Incidence and prevalence of Alzheimer's disease or dementia using an illness-death model
    • Commenges, D., Joly, P., Letenneur, L. & Dartigues, J. F. (2004). Incidence and prevalence of Alzheimer's disease or dementia using an illness-death model. Statist. Med. 23, 199-210.
    • (2004) Statist. Med , vol.23 , pp. 199-210
    • Commenges, D.1    Joly, P.2    Letenneur, L.3    Dartigues, J.F.4
  • 10
    • 0000541146 scopus 로고
    • Asymptotic analysis of penalized likelihood and related estimators
    • Cox, D. & O'Sullivan, F. (1990). Asymptotic analysis of penalized likelihood and related estimators. Ann. Statist. 18, 1676-1695.
    • (1990) Ann. Statist , vol.18 , pp. 1676-1695
    • Cox, D.1    O'Sullivan, F.2
  • 11
    • 0033233732 scopus 로고    scopus 로고
    • Optimal convergence rates for Good's nonparametric likelihood density estimator
    • Eggermont, P. & LaRiccia, V. (1999). Optimal convergence rates for Good's nonparametric likelihood density estimator. Ann. Statist. 27, 1600-1615.
    • (1999) Ann. Statist , vol.27 , pp. 1600-1615
    • Eggermont, P.1    LaRiccia, V.2
  • 13
    • 0001206510 scopus 로고    scopus 로고
    • Coarsening at random: Characterizations, conjectures and counter-examples
    • State of the art in survival analysis, eds D.-Y. Lin & T. R. Fleming, Springer-Verlag, New York
    • Gill, R. D., van der Laan, M. J. & Robins, J. M. (1997). Coarsening at random: characterizations, conjectures and counter-examples. In State of the art in survival analysis, Springer Lecture Notes in Statistics 123 (eds D.-Y. Lin & T. R. Fleming), 255-294. Springer-Verlag, New York.
    • (1997) Springer Lecture Notes in Statistics , vol.123 , pp. 255-294
    • Gill, R.D.1    van der Laan, M.J.2    Robins, J.M.3
  • 14
    • 0000451036 scopus 로고
    • Nonparametric roughness penalty for probability densities
    • Good, I. J. & Gaskins, R. A. (1971). Nonparametric roughness penalty for probability densities. Biometrika 58, 255-277.
    • (1971) Biometrika , vol.58 , pp. 255-277
    • Good, I.J.1    Gaskins, R.A.2
  • 15
    • 21444456230 scopus 로고    scopus 로고
    • Penalized likelihood hazard estimation: A general procedure
    • Gu, C. (1996). Penalized likelihood hazard estimation: a general procedure. Statist. Sinica 6, 861-876.
    • (1996) Statist. Sinica , vol.6 , pp. 861-876
    • Gu, C.1
  • 16
    • 0000418028 scopus 로고
    • On Kullback-Leibler loss and density estimation
    • Hall, P. (1987). On Kullback-Leibler loss and density estimation. Ann. Statist. 15, 1491-1519.
    • (1987) Ann. Statist , vol.15 , pp. 1491-1519
    • Hall, P.1
  • 18
    • 0000531113 scopus 로고
    • Multivariate point processes: Predictable projection; Radon-Nikodym derivative, representation of martingales
    • Jacod, J. (1975). Multivariate point processes: predictable projection; Radon-Nikodym derivative, representation of martingales. Z. Wahrsch. verw Geb. 31, 235-253.
    • (1975) Z. Wahrsch. verw Geb , vol.31 , pp. 235-253
    • Jacod, J.1
  • 19
    • 0032887315 scopus 로고    scopus 로고
    • A penalized likelihood approach for a progressive three-state model with censored and truncated data: Application to AIDS
    • Joly, P. & Commenges, D. (1999). A penalized likelihood approach for a progressive three-state model with censored and truncated data: application to AIDS. Biometrics 55, 887-890.
    • (1999) Biometrics , vol.55 , pp. 887-890
    • Joly, P.1    Commenges, D.2
  • 20
    • 0347867151 scopus 로고    scopus 로고
    • A penalized likelihood approach for an illness-death model with interval-censored data: Application to age-specific incidence of dementia
    • Joly, P., Commenges, D., Helmer, C. & Letenneur, L. (2002). A penalized likelihood approach for an illness-death model with interval-censored data: application to age-specific incidence of dementia. Biostatistics 3, 433-443.
    • (2002) Biostatistics , vol.3 , pp. 433-443
    • Joly, P.1    Commenges, D.2    Helmer, C.3    Letenneur, L.4
  • 22
    • 0031455187 scopus 로고    scopus 로고
    • Hazard regression with interval-censored data
    • Kooperberg, C. & Clarkson, D. B. (1997). Hazard regression with interval-censored data. Biometrics 53, 1485-1494.
    • (1997) Biometrics , vol.53 , pp. 1485-1494
    • Kooperberg, C.1    Clarkson, D.B.2
  • 25
    • 0017892071 scopus 로고
    • Semi-Markov models for partially censored data
    • Lagakos, S. W., Sommer, C. J. & Zelen, M. (1978). Semi-Markov models for partially censored data. Biometrika 65, 311-317.
    • (1978) Biometrika , vol.65 , pp. 311-317
    • Lagakos, S.W.1    Sommer, C.J.2    Zelen, M.3
  • 27
    • 0032910570 scopus 로고    scopus 로고
    • Are sex and educational level independent predictors of dementia and Alzheimer's disease? Incidence data from the PAQUID project
    • Letenneur, L., Gilleron, V., Commenges, D., Helmer, C., Orgogozo, J. M. & Dartigues, J. F. (1999). Are sex and educational level independent predictors of dementia and Alzheimer's disease? Incidence data from the PAQUID project. J. Neurol. Neurosurg. Psychiatr. 66, 177-183.
    • (1999) J. Neurol. Neurosurg. Psychiatr , vol.66 , pp. 177-183
    • Letenneur, L.1    Gilleron, V.2    Commenges, D.3    Helmer, C.4    Orgogozo, J.M.5    Dartigues, J.F.6
  • 28
    • 14844316652 scopus 로고    scopus 로고
    • Estimating the expectation of the log-likelihood with censored data for estimator selection
    • Liquet, B. & Commenges, D. (2004). Estimating the expectation of the log-likelihood with censored data for estimator selection. Lifetime Data Anal. 10, 351-367.
    • (2004) Lifetime Data Anal , vol.10 , pp. 351-367
    • Liquet, B.1    Commenges, D.2
  • 29
    • 0037368564 scopus 로고    scopus 로고
    • Bootstrap choice of estimators in parametric and semi-parametric families: An extension of EIC
    • Liquet, B., Sakarovitch, C. & Commenges, D. (2003). Bootstrap choice of estimators in parametric and semi-parametric families: an extension of EIC. Biometrics 59, 172-178.
    • (2003) Biometrics , vol.59 , pp. 172-178
    • Liquet, B.1    Sakarovitch, C.2    Commenges, D.3
  • 30
    • 33847392609 scopus 로고    scopus 로고
    • Selection between proportional and stratified hazards models based on expected log-likelihood
    • in press
    • Liquet, B., Saracco, J. & Commenges, D. (2006). Selection between proportional and stratified hazards models based on expected log-likelihood. Comput. Statist., in press.
    • (2006) Comput. Statist
    • Liquet, B.1    Saracco, J.2    Commenges, D.3
  • 31
    • 19744372814 scopus 로고    scopus 로고
    • Generalized functional linear models
    • Müller, H. G. & Stadtmüller, U. (2005). Generalized functional linear models. Ann. Statist. 33, 774-805.
    • (2005) Ann. Statist , vol.33 , pp. 774-805
    • Müller, H.G.1    Stadtmüller, U.2
  • 32
    • 0001047094 scopus 로고
    • Fast computation of fully automated log-density and log-hazard estimators
    • O'Sullivan, F. (1988). Fast computation of fully automated log-density and log-hazard estimators. SIAM J. Sci. Comput. 9, 363-379.
    • (1988) SIAM J. Sci. Comput , vol.9 , pp. 363-379
    • O'Sullivan, F.1
  • 33
    • 0000895861 scopus 로고
    • Smoothing counting process intensities by means of kernel functions
    • Ramlau-Hansen, H. (1983). Smoothing counting process intensities by means of kernel functions. Ann. Statist. 11, 453-466.
    • (1983) Ann. Statist , vol.11 , pp. 453-466
    • Ramlau-Hansen, H.1
  • 34
    • 0035470896 scopus 로고    scopus 로고
    • A generalized additive regression model for survival analysis
    • Scheike, T. (2001). A generalized additive regression model for survival analysis. Ann. Statist. 29, 1344-1380.
    • (2001) Ann. Statist , vol.29 , pp. 1344-1380
    • Scheike, T.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.