-
1
-
-
63249122661
-
Mortality results from a randomized prostate-cancer screening trial
-
G.L. Andriole, E.D. Crawford, R.L. Grubb, S.S. Buys, D. Chia, T.R. Church, M.N. Fouad, E.P. Gelmann, P.A. Kvale, D.J. Reding, J.L. Weissfeld, L.A. Yokochi, B. O'Brien, J.D. Clapp, J.M. Rathmell, T.L. Riley, R.B. Hayes, B.S. Kramer, G. Izmirlian, A.B. Miller, P.F. Pinsky, P.C. Prorok, J.K. Gohagan, and C.D. Berg, M.D. for the PLCO Project Team, Mortality results from a randomized prostate-cancer screening trial, New England J. Med. 360 (2009), pp. 1310–1319. doi: 10.1056/NEJMoa0810696
-
(2009)
New England J. Med.
, vol.360
, pp. 1310-1319
-
-
Andriole, G.L.1
Crawford, E.D.2
Grubb, R.L.3
Buys, S.S.4
Chia, D.5
Church, T.R.6
Fouad, M.N.7
Gelmann, E.P.8
Kvale, P.A.9
Reding, D.J.10
Weissfeld, J.L.11
Yokochi, L.A.12
O'Brien, B.13
Clapp, J.D.14
Rathmell, J.M.15
Riley, T.L.16
Hayes, R.B.17
Kramer, B.S.18
Izmirlian, G.19
Miller, A.B.20
Pinsky, P.F.21
Prorok, P.C.22
Gohagan, J.K.23
Berg, C.D.24
more..
-
2
-
-
4043150795
-
The interplay of Bayesian and Frequentist analysis
-
M.J. Bayarri and J.O. Berger, The interplay of Bayesian and Frequentist analysis, Statist. Sci. 19 (2004), pp. 58–80. doi: 10.1214/088342304000000116
-
(2004)
Statist. Sci.
, vol.19
, pp. 58-80
-
-
Bayarri, M.J.1
Berger, J.O.2
-
3
-
-
17444422242
-
Screening for prostate cancer by using random-effects models
-
L.J. Brant, S.L. Sheng, C.H. Morrell, G.N. Verbeke, E. Lesaffre, and H.B. Carter, Screening for prostate cancer by using random-effects models, J. R. Statist. Soc: Ser. A (Stat. Soc.) 166 (2003), pp. 51–62. doi: 10.1111/1467-985X.00258
-
(2003)
J. R. Statist. Soc: Ser. A (Stat. Soc.)
, vol.166
, pp. 51-62
-
-
Brant, L.J.1
Sheng, S.L.2
Morrell, C.H.3
Verbeke, G.N.4
Lesaffre, E.5
Carter, H.B.6
-
4
-
-
84880005911
-
Early detection of prostate cancer: Aua guideline
-
H.B. Carter, P.C. Albertsen, M.J. Barry, R. Etzioni, S.J. Freedland, K.L. Greene, L. Holmberg, P. Kantoff, B.R. Konety, M.H. Murad, D.F. Penson, and A.L. Zietman, Early detection of prostate cancer: Aua guideline, Am. Urological Assoc. 190 (2013), pp. 419–426.
-
(2013)
Am. Urological Assoc.
, vol.190
, pp. 419-426
-
-
Carter, H.B.1
Albertsen, P.C.2
Barry, M.J.3
Etzioni, R.4
Freedland, S.J.5
Greene, K.L.6
Holmberg, L.7
Kantoff, P.8
Konety, B.R.9
Murad, M.H.10
Penson, D.F.11
Zietman, A.L.12
-
5
-
-
84921386393
-
Reconciling Bayesian and Frequentist evidence in the one-sided testing problem
-
G. Casella and R.L. Berger, Reconciling Bayesian and Frequentist evidence in the one-sided testing problem, J. American Statist. Assoc. 82 (1987), pp. 106–111. doi: 10.1080/01621459.1987.10478396
-
(1987)
J. American Statist. Assoc.
, vol.82
, pp. 106-111
-
-
Casella, G.1
Berger, R.L.2
-
6
-
-
84924897049
-
-
stjm: Stata module to fit shared parameter joint models of longitudinal and survival data, 2012
-
M.J. Crowther, stjm: Stata module to fit shared parameter joint models of longitudinal and survival data, 2012. http://ideas.repec.org/c/boc/bocode/s457342.html.
-
-
-
Crowther, M.J.1
-
7
-
-
38949085322
-
Quantifying the role of PSA screening in the US prostate cancer mortality decline
-
R. Etzioni, A. Tsodikov, A. Mariotto, A. Szabo, S. Falcon, J. Wegelin, D. diTommaso, K. Karnofski, R. Gulati, D.F. Penson, and E. Feuer, Quantifying the role of PSA screening in the US prostate cancer mortality decline, Cancer Causes Control 19 (2008), pp. 175–181. doi: 10.1007/s10552-007-9083-8
-
(2008)
Cancer Causes Control
, vol.19
, pp. 175-181
-
-
Etzioni, R.1
Tsodikov, A.2
Mariotto, A.3
Szabo, A.4
Falcon, S.5
Wegelin, J.6
diTommaso, D.7
Karnofski, K.8
Gulati, R.9
Penson, D.F.10
Feuer, E.11
-
8
-
-
0029763749
-
Simultaneously modelling censored survival data and repeatedly measured covariates: A Gibbs sampling approach
-
C.L. Faucett and D.C. Thomas, Simultaneously modelling censored survival data and repeatedly measured covariates: A Gibbs sampling approach, Stat. Med. 15 (1996), pp. 1663–1685. doi: 10.1002/(SICI)1097-0258(19960815)15:15<1663::AID-SIM294>3.0.CO;2-1
-
(1996)
Stat. Med.
, vol.15
, pp. 1663-1685
-
-
Faucett, C.L.1
Thomas, D.C.2
-
9
-
-
38149135632
-
A joint latent class changepoint model to improve the prediction of time to graft failure
-
F.G. Garre, A.H. Zwinderman, R.B. Geskus, and Y.W. Sijpkens, A joint latent class changepoint model to improve the prediction of time to graft failure, J. R. Statist. Soc: Ser. A (Stat. Soc.) 171 (2008), pp. 299–308.
-
(2008)
J. R. Statist. Soc: Ser. A (Stat. Soc.)
, vol.171
, pp. 299-308
-
-
Garre, F.G.1
Zwinderman, A.H.2
Geskus, R.B.3
Sijpkens, Y.W.4
-
10
-
-
0000710136
-
Joint modelling of longitudinal measurements and event time data
-
R. Henderson, P. Diggle, and A. Dobson, Joint modelling of longitudinal measurements and event time data, Biostatistics 1 (2000), pp. 465–480. doi: 10.1093/biostatistics/1.4.465
-
(2000)
Biostatistics
, vol.1
, pp. 465-480
-
-
Henderson, R.1
Diggle, P.2
Dobson, A.3
-
11
-
-
70349637766
-
Prostate specific antigen for early detection of prostate cancer: Longitudinal study
-
B. Holmstrom, M. Johansson, A. Bergh, U.-H. Stenman, G. Hallmans, and P. Stattin, Prostate specific antigen for early detection of prostate cancer: Longitudinal study, BMJ 339 (2009), pp. b3537. doi: 10.1136/bmj.b3537
-
(2009)
BMJ
, vol.339
, pp. 3537
-
-
Holmstrom, B.1
Johansson, M.2
Bergh, A.3
Stenman, U.-H.4
Hallmans, G.5
Stattin, P.6
-
12
-
-
84874858347
-
Screening for prostate cancer
-
D. Ilic, M.M. Neuberger, M. Djulbegovic, and P. Dahm, Screening for prostate cancer, Cochrane Database Systematic Rev. 1 (2013), pp. CD004720. Available at http://www.ncbi.nlm.nih.gov/pubmed/23440794/.
-
(2013)
Cochrane Database Systematic Rev.
, vol.1
, pp. 4720
-
-
Ilic, D.1
Neuberger, M.M.2
Djulbegovic, M.3
Dahm, P.4
-
13
-
-
84863725759
-
An examination of the dynamic changes in prostate-specific antigen occurring in a population-based cohort of men over time
-
B.A. Inman, J. Zhang, N.D. Shah, and B.T. Denton, An examination of the dynamic changes in prostate-specific antigen occurring in a population-based cohort of men over time, BJU Int. 110 (2012), pp. 375–381. doi: 10.1111/j.1464-410X.2011.10925.x
-
(2012)
BJU Int.
, vol.110
, pp. 375-381
-
-
Inman, B.A.1
Zhang, J.2
Shah, N.D.3
Denton, B.T.4
-
14
-
-
21644490251
-
Combining longitudinal studies of PSA
-
L.Y.T. Inoue, R. Etzioni, E.H. Slate, C. Morrell, and D.F. Penson, Combining longitudinal studies of PSA, Biostatistics 5 (2004), pp. 483–500. doi: 10.1093/biostatistics/kxh003
-
(2004)
Biostatistics
, vol.5
, pp. 483-500
-
-
Inoue, L.Y.T.1
Etzioni, R.2
Slate, E.H.3
Morrell, C.4
Penson, D.F.5
-
15
-
-
42349097208
-
Modeling disease progression with longitudinal markers
-
L.Y.T Inoue, R. Etzioni, C. Morrell, and P. Müller, Modeling disease progression with longitudinal markers, J. Am. Statist. Assoc. 103 (2008), pp. 259–270. doi: 10.1198/016214507000000356
-
(2008)
J. Am. Statist. Assoc.
, vol.103
, pp. 259-270
-
-
Inoue, L.Y.T.1
Etzioni, R.2
Morrell, C.3
Müller, P.4
-
16
-
-
82955235039
-
Statistical inference: The big picture
-
R.E. Kass, Statistical inference: The big picture, Statist. Sci. 26 (2011), pp. 1–9. doi: 10.1214/10-STS337
-
(2011)
Statist. Sci.
, vol.26
, pp. 1-9
-
-
Kass, R.E.1
-
17
-
-
0042485002
-
The joint modeling of a longitudinal disease progression marker and the failure time process in the presence of cure
-
N.J. Law, J.M.G. Taylor, and H. Sandler, The joint modeling of a longitudinal disease progression marker and the failure time process in the presence of cure, Biostatistics 3 (2002), pp. 547–563. doi: 10.1093/biostatistics/3.4.547
-
(2002)
Biostatistics
, vol.3
, pp. 547-563
-
-
Law, N.J.1
Taylor, J.M.G.2
Sandler, H.3
-
18
-
-
34249822549
-
Data cloning: Easy maximum likelihood estimation for complex ecological models using Bayesian Markov chain Monte Carlo methods
-
S.R. Lele, B. Dennis, and F. Lutscher, Data cloning: Easy maximum likelihood estimation for complex ecological models using Bayesian Markov chain Monte Carlo methods, Ecol. Lett. 10 (2007), pp. 551–563. doi: 10.1111/j.1461-0248.2007.01047.x
-
(2007)
Ecol. Lett.
, vol.10
, pp. 551-563
-
-
Lele, S.R.1
Dennis, B.2
Lutscher, F.3
-
19
-
-
0036489045
-
Latent class models for joint analysis of longitudinal biomarker and event process data: Application to longitudinal prostate-specific antigen readings and prostate cancer
-
H. Lin, B.W. Turnbull, C.E. McCulloch, and E.H. Slate, Latent class models for joint analysis of longitudinal biomarker and event process data: Application to longitudinal prostate-specific antigen readings and prostate cancer, J. Am. Statist. Assoc. 97 (2002), pp. 53–65. doi: 10.1198/016214502753479220
-
(2002)
J. Am. Statist. Assoc.
, vol.97
, pp. 53-65
-
-
Lin, H.1
Turnbull, B.W.2
McCulloch, C.E.3
Slate, E.H.4
-
20
-
-
33747474436
-
Calibrated Bayes: A Bayes/frequentist roadmap
-
R.J. Little, Calibrated Bayes: A Bayes/frequentist roadmap, Am. Statist. 60 (2006), pp. 213–223. doi: 10.1198/000313006X117837
-
(2006)
Am. Statist.
, vol.60
, pp. 213-223
-
-
Little, R.J.1
-
21
-
-
84863517227
-
Mortality due to prostate cancer in the spanish arm of the european randomized study of screening for prostate cancer (ERSPC). Results after a 15-year follow-up
-
M. Lujan, A. Paez, A. Berenguer, and J.A. Rodriguez, Mortality due to prostate cancer in the spanish arm of the european randomized study of screening for prostate cancer (ERSPC). Results after a 15-year follow-up, Actas Urológicas Españolas 36 (2012), pp. 403–409.
-
(2012)
Actas Urológicas Españolas
, vol.36
, pp. 403-409
-
-
Lujan, M.1
Paez, A.2
Berenguer, A.3
Rodriguez, J.A.4
-
22
-
-
0006407254
-
WinBUGS – A Bayesian modelling framework: Concepts, structure, and extensibility
-
D.J. Lunn, A. Thomas, N. Best, and D. Spiegelhalter, WinBUGS – A Bayesian modelling framework: Concepts, structure, and extensibility, Stat. Comput. 10 (2000), pp. 325–337. doi: 10.1023/A:1008929526011
-
(2000)
Stat. Comput.
, vol.10
, pp. 325-337
-
-
Lunn, D.J.1
Thomas, A.2
Best, N.3
Spiegelhalter, D.4
-
23
-
-
84859772296
-
Screening for prostate cancer using multivariate mixed-effects models
-
C.H. Morrell, L.J. Brant, S. Sheng, and E.J. Metter, Screening for prostate cancer using multivariate mixed-effects models, J. Appl. Stat. 39 (2012), pp. 1151–1175. doi: 10.1080/02664763.2011.644523
-
(2012)
J. Appl. Stat.
, vol.39
, pp. 1151-1175
-
-
Morrell, C.H.1
Brant, L.J.2
Sheng, S.3
Metter, E.J.4
-
24
-
-
85008794156
-
A review on joint models in biometrical research
-
A. Neuhaus, T. Augustin, C. Heumann, and D. Daumer, A review on joint models in biometrical research, J. Statist. Theory Pract. 3 (2009), pp. 855–868. doi: 10.1080/15598608.2009.10411965
-
(2009)
J. Statist. Theory Pract.
, vol.3
, pp. 855-868
-
-
Neuhaus, A.1
Augustin, T.2
Heumann, C.3
Daumer, D.4
-
25
-
-
84924897048
-
-
Joiner: Joint modelling of repeated measurements and time-to-event data, 2012
-
P. Philipson, I. Sousa, P. Diggle, P. Williamson, R. Kolamunnage-Dona, and R. Henderson, Joiner: Joint modelling of repeated measurements and time-to-event data, 2012. Available at http://www.people.fas.harvard.edu/~sfinch/csolve/ou.pdf.
-
-
-
Philipson, P.1
Sousa, I.2
Diggle, P.3
Williamson, P.4
Kolamunnage-Dona, R.5
Henderson, R.6
-
26
-
-
84946045727
-
Approximations to the log-likelihood function in the nonlinear mixed-effects model
-
J.C. Pinheiro and D.M. Bates, Approximations to the log-likelihood function in the nonlinear mixed-effects model, J. Comput. Graph. Stat. 4 (1995), pp. 12–35.
-
(1995)
J. Comput. Graph. Stat.
, vol.4
, pp. 12-35
-
-
Pinheiro, J.C.1
Bates, D.M.2
-
27
-
-
84924897047
-
-
JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling, 3rd International Workshop on Distributed Statistical Computing (DSC 2003), 2003
-
M. Plummer, JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling, 3rd International Workshop on Distributed Statistical Computing (DSC 2003), 2003.
-
-
-
Plummer, M.1
-
28
-
-
77749317069
-
Covariate measurement errors and parameter estimation in a failure time regression model
-
R.L. Prentice, Covariate measurement errors and parameter estimation in a failure time regression model, Biometrika 69 (1982), pp. 331–342. doi: 10.1093/biomet/69.2.331
-
(1982)
Biometrika
, vol.69
, pp. 331-342
-
-
Prentice, R.L.1
-
29
-
-
70149108170
-
Development and validation of a dynamic prognostic tool for prostate cancer recurrence using repeated measures of posttreatment PSA: A joint modeling approach
-
C. Proust-Lima and J.M.G. Taylor, Development and validation of a dynamic prognostic tool for prostate cancer recurrence using repeated measures of posttreatment PSA: A joint modeling approach, Biostatistics 10 (2009), pp. 535–549. doi: 10.1093/biostatistics/kxp009
-
(2009)
Biostatistics
, vol.10
, pp. 535-549
-
-
Proust-Lima, C.1
Taylor, J.M.G.2
-
30
-
-
84892600752
-
Joint latent class models for longitudinal and time-to-event data: A review
-
C. Proust-Lima, M. Séne, J.M. Taylor, and H. Jacqmin-Gadda, Joint latent class models for longitudinal and time-to-event data: A review, Stat Methods Med Res 23 (2014), pp. 74–90. doi: 10.1177/0962280212445839
-
(2014)
Stat Methods Med Res
, vol.23
, pp. 74-90
-
-
Proust-Lima, C.1
Séne, M.2
Taylor, J.M.3
Jacqmin-Gadda, H.4
-
31
-
-
77955157844
-
JM: An R package for the joint modelling of longitudinal and time-to-event data
-
D. Rizopoulos, JM: An R package for the joint modelling of longitudinal and time-to-event data, J. Statist. Softw. 35 (2010), pp. 1–33. Available at http://www.jstatsoft.org/v35/i09/.
-
(2010)
J. Statist. Softw.
, vol.35
, pp. 1-33
-
-
Rizopoulos, D.1
-
32
-
-
80052787679
-
Dynamic predictions and prospective accuracy in joint models for longitudinal and time-to-event data
-
D. Rizopoulos, Dynamic predictions and prospective accuracy in joint models for longitudinal and time-to-event data, Biometrics 67 (2011), pp. 819–829. doi: 10.1111/j.1541-0420.2010.01546.x
-
(2011)
Biometrics
, vol.67
, pp. 819-829
-
-
Rizopoulos, D.1
-
33
-
-
80455176985
-
Fast fitting of joint models for longitudinal and event time data using a pseudo-adaptive Gaussian quadrature rule
-
D. Rizopoulos, Fast fitting of joint models for longitudinal and event time data using a pseudo-adaptive Gaussian quadrature rule, Comput. Stat. Data Anal. 56 (2012), pp. 491–501. doi: 10.1016/j.csda.2011.09.007
-
(2012)
Comput. Stat. Data Anal.
, vol.56
, pp. 491-501
-
-
Rizopoulos, D.1
-
35
-
-
84924897046
-
-
JMbayes: Shared parameter models for the joint modeling of longitudinal and time-to-event data using JAGS, WinBUGS, or OpenBUGS. R package 0.4-1
-
D. Rizopoulos, JMbayes: Shared parameter models for the joint modeling of longitudinal and time-to-event data using JAGS, WinBUGS, or OpenBUGS. R package 0.4-1, 2013. Available at http://cran.r-project.org/package=JMbayes/.
-
-
-
Rizopoulos, D.1
-
36
-
-
79955847737
-
A Bayesian semiparametric multivariate joint model for multiple longitudinal outcomes and a time-to-event
-
D. Rizopoulos and P. Ghosh, A Bayesian semiparametric multivariate joint model for multiple longitudinal outcomes and a time-to-event, Stat. Med. 30 (2011), pp. 1366–1380. doi: 10.1002/sim.4205
-
(2011)
Stat. Med.
, vol.30
, pp. 1366-1380
-
-
Rizopoulos, D.1
Ghosh, P.2
-
37
-
-
84856380113
-
Prediction of prostate cancer risk: The role of prostate volume and digital rectal examination in the ERSPC risk calculators
-
M.J. Roobol, H.A. van Vugt, S. Loeb, X. Zhu, M. Bul, Chris H. Bangma, Arno G.L.J.H. van Leenders, E.W. Steyerberg, and F.H. Schröder, Prediction of prostate cancer risk: The role of prostate volume and digital rectal examination in the ERSPC risk calculators, Eur. Urology 61 (2012), pp. 577–583. doi: 10.1016/j.eururo.2011.11.012
-
(2012)
Eur. Urology
, vol.61
, pp. 577-583
-
-
Roobol, M.J.1
van Vugt, H.A.2
Loeb, S.3
Zhu, X.4
Bul, M.5
Bangma, C.H.6
van Leenders, A.G.L.J.H.7
Steyerberg, E.W.8
Schröder, F.H.9
-
38
-
-
45849109563
-
The comparability of models for predicting the risk of a positive prostate biopsy with prostate-specific antigen alone: A systematic review
-
F. Schröder and M.W. Kattan, The comparability of models for predicting the risk of a positive prostate biopsy with prostate-specific antigen alone: A systematic review, Eur. Urology 54 (2008), pp. 274–290. doi: 10.1016/j.eururo.2008.05.022
-
(2008)
Eur. Urology
, vol.54
, pp. 274-290
-
-
Schröder, F.1
Kattan, M.W.2
-
39
-
-
84858212484
-
Prostate-cancer mortality at 11 years of follow-up
-
F.H. Schröder, J. Hugosson, M.J. Roobol, T.L.J. Tammela, S. Ciatto, V. Nelen, M. Kwiatkowski, M. Lujan, H. Lilja, M. Zappa, L.J. Denis, F. Recker, A. Páez, L. Määttänen, C.H. Bangma, G. Aus, S. Carlsson, A. Villers, X. Rebillard, T. van der Kwast, P.M. Kujala, B.G. Blijenberg, U.-H. Stenman, A. Huber, K. Taari, M. Hakama, S.M. Moss, H.J. de Koning, and A. Auvinen, M.D. for the ERSPC Investigators, Prostate-cancer mortality at 11 years of follow-up, New Engl. J. Med. 366 (2012), pp. 981–990. doi: 10.1056/NEJMoa1113135
-
(2012)
New Engl. J. Med.
, vol.366
, pp. 981-990
-
-
Schröder, F.H.1
Hugosson, J.2
Roobol, M.J.3
Tammela, T.L.J.4
Ciatto, S.5
Nelen, V.6
Kwiatkowski, M.7
Lujan, M.8
Lilja, H.9
Zappa, M.10
Denis, L.J.11
Recker, F.12
Páez, A.13
Määttänen, L.14
Bangma, C.H.15
Aus, G.16
Carlsson, S.17
Villers, A.18
Rebillard, X.19
van der Kwast, T.20
Kujala, P.M.21
Blijenberg, B.G.22
Stenman, U.-H.23
Huber, A.24
Taari, K.25
Hakama, M.26
Moss, S.M.27
de Koning, H.J.28
Auvinen, A.29
more..
-
40
-
-
84875937581
-
Real-time individual predictions of prostate cancer recurrence using joint models
-
J.M.G. Taylor, Y. Park, D.P. Ankerst, C. Proust-Lima, S. Williams, L. Kestin, K. Bae, T. Pickles, and H. Sandler, Real-time individual predictions of prostate cancer recurrence using joint models, Biometrics 69 (2013), pp. 206–213. doi: 10.1111/j.1541-0420.2012.01823.x
-
(2013)
Biometrics
, vol.69
, pp. 206-213
-
-
Taylor, J.M.G.1
Park, Y.2
Ankerst, D.P.3
Proust-Lima, C.4
Williams, S.5
Kestin, L.6
Bae, K.7
Pickles, T.8
Sandler, H.9
-
42
-
-
8644246036
-
Joint modeling of longitudinal and time-to-event data: An overview
-
A.A. Tsiatis and M. Davidian, Joint modeling of longitudinal and time-to-event data: An overview, Statist. Sin. 14 (2004), pp. 809–834.
-
(2004)
Statist. Sin.
, vol.14
, pp. 809-834
-
-
Tsiatis, A.A.1
Davidian, M.2
-
43
-
-
21844506206
-
Modeling the relationship of survival to longitudinal data measured with error. Applications to survival and CD4 counts in patients with AIDS
-
A.A. Tsiatis, V. Degruttola, and M.S. Wulfsohn, Modeling the relationship of survival to longitudinal data measured with error. Applications to survival and CD4 counts in patients with AIDS, J. Am. Statist. Assoc. 90 (1995), pp. 27–37. doi: 10.1080/01621459.1995.10476485
-
(1995)
J. Am. Statist. Assoc.
, vol.90
, pp. 27-37
-
-
Tsiatis, A.A.1
Degruttola, V.2
Wulfsohn, M.S.3
-
44
-
-
80655144776
-
Re: An empirical evaluation of guidelines on prostate-specific antigen velocity in prostate cancer detection
-
A.J. Vickers, Re: An empirical evaluation of guidelines on prostate-specific antigen velocity in prostate cancer detection, J. Nat. Cancer Inst. 103 (2011), pp. 1635–1636. doi: 10.1093/jnci/djr353
-
(2011)
J. Nat. Cancer Inst.
, vol.103
, pp. 1635-1636
-
-
Vickers, A.J.1
-
45
-
-
35348823195
-
The predictive value of prostate cancer biomarkers depends on age and time to diagnosis: Towards a biologically-based screening strategy
-
A.J. Vickers, D. Ulmert, A.M. Serio, T. Bjork, Peter T. Scardino, James A. Eastham, G. Berglund, and H. Lilja, The predictive value of prostate cancer biomarkers depends on age and time to diagnosis: Towards a biologically-based screening strategy, Int. J. Cancer 121 (2007), pp. 2212–2217. doi: 10.1002/ijc.22956
-
(2007)
Int. J. Cancer
, vol.121
, pp. 2212-2217
-
-
Vickers, A.J.1
Ulmert, D.2
Serio, A.M.3
Bjork, T.4
Scardino, P.T.5
Eastham, J.A.6
Berglund, G.7
Lilja, H.8
-
46
-
-
0030893266
-
A joint model for survival and longitudinal data measured with error
-
M.S. Wulfsohn and A.A. Tsiatis, A joint model for survival and longitudinal data measured with error, Biometrics 53 (1997), pp. 330–339. doi: 10.2307/2533118
-
(1997)
Biometrics
, vol.53
, pp. 330-339
-
-
Wulfsohn, M.S.1
Tsiatis, A.A.2
-
47
-
-
8644269772
-
Joint longitudinal-survival-cure models and their application to prostate cancer
-
M. Yu, N. Law, J. Taylor, and H. Sandler, Joint longitudinal-survival-cure models and their application to prostate cancer, Statist. Sin. 14 (2004), pp. 835–862.
-
(2004)
Statist. Sin.
, vol.14
, pp. 835-862
-
-
Yu, M.1
Law, N.2
Taylor, J.3
Sandler, H.4
|