-
1
-
-
34247258392
-
Surrogate marker evaluation from an information theory perspective
-
ALONSO, A. AND MOLENBERGHS, G. (2007). Surrogate marker evaluation from an information theory perspective. Biometrics 1, 180-186.
-
(2007)
Biometrics
, vol.1
, pp. 180-186
-
-
Alonso, A.1
Molenberghs, G.2
-
2
-
-
52649180045
-
Evaluating time to cancer recurrence as a surrogate marker for survival from an information theory perspective
-
ALONSO, A. AND MOLENBERGHS, G. (2008). Evaluating time to cancer recurrence as a surrogate marker for survival from an information theory perspective. Statistical Methods in Medical Research 17, 497-504.
-
(2008)
Statistical Methods in Medical Research
, vol.17
, pp. 497-504
-
-
Alonso, A.1
Molenberghs, G.2
-
3
-
-
52649123777
-
Two simple approaches for validating a binary surrogate endpoint using data from multiple trials
-
BAKER, S. G. (2008). Two simple approaches for validating a binary surrogate endpoint using data from multiple trials. Statistical Methodsin Medical Research 17, 505-514.
-
(2008)
Statistical Methodsin Medical Research
, vol.17
, pp. 505-514
-
-
Baker, S.G.1
-
4
-
-
0031708453
-
Criteria for the validation of surrogate endpoints in randomized experiments
-
DOI 10.2307/2533853
-
BUYSE, M. AND MOLENBERGHS, G. (1998). Criteria for the validation of surrogate endpoints in randomized experiments. Biometrics 54, 1014-1029. (Pubitemid 28429294)
-
(1998)
Biometrics
, vol.54
, Issue.3
, pp. 1014-1029
-
-
Buyse, M.1
Molenberghs, G.2
-
5
-
-
0001863948
-
The validation of surrogate endpoints in meta-analyses ofrandomized experiments
-
BUYSE, M., MOLENBERGHS, G., BURZYKOWSKI, T., RENARD, D. AND GEYS, H. (2000). The validation of surrogate endpoints in meta-analyses ofrandomized experiments. Biostatistics 1, 49-67.
-
(2000)
Biostatistics
, vol.1
, pp. 49-67
-
-
Buyse, M.1
Molenberghs, G.2
Burzykowski, T.3
Renard, D.4
Geys, H.5
-
6
-
-
70450277983
-
Deviance information criteria for missing data models
-
CELEUX, G., FORBES, F., ROBERT, C. P. AND TITTERINGTON, D. M. (2006). Deviance information criteria for missing data models. Bayesian Analysis 1, 651-674.
-
(2006)
Bayesian Analysis
, vol.1
, pp. 651-674
-
-
Celeux, G.1
Forbes, F.2
Robert, C.P.3
Titterington, D.M.4
-
7
-
-
0030777744
-
Meta-analysis for the evaluation of potential surrogate markers
-
DOI 10.1002/(SICI)1097-0258(19970915)16:17<1965::AID-SIM630>3.0. CO;2-M
-
DANIELS, M. J. AND HUGHES, M. D. (1997). Meta-analysis for the evaluation of potential surrogate markers. Statistics in Medicine 16, 1965-1982. (Pubitemid 27397267)
-
(1997)
Statistics in Medicine
, vol.16
, Issue.17
, pp. 1965-1982
-
-
Daniels, M.J.1
Hughes, M.D.2
-
8
-
-
0036188782
-
Principal stratifcation in casual inference
-
FRANGAKIS, C. E. AND RUBIN, D. B. (2002). Principal stratifcation in casual inference. Biometrics 58, 21-29.
-
(2002)
Biometrics
, vol.58
, pp. 21-29
-
-
Frangakis, C.E.1
Rubin, D.B.2
-
9
-
-
0026573094
-
Statistical validation ofintermediate endpoints for chronic disease
-
FREEDMAN, L. S., GRAUBARD, B. I. AND SCHATZKIN, A. (1992). Statistical validation ofintermediate endpoints for chronic disease. Statistics in Medicine 11, 167-178.
-
(1992)
Statistics in Medicine
, vol.11
, pp. 167-178
-
-
Freedman, L.S.1
Graubard, B.I.2
Schatzkin, A.3
-
10
-
-
0033636097
-
Latent class model diagnosis
-
GARRET, E. S. AND ZEGER, S. L (2000). Latent class model diagnosis. Biometrics 56, 1055-1067.
-
(2000)
Biometrics
, vol.56
, pp. 1055-1067
-
-
Garret, E.S.1
Zeger, S.L.2
-
11
-
-
66949156958
-
Evaluating causal effect predictiveness of candidate surrogate endpoints
-
GILBERT, P. B. AND HUDGENS, M. G. (2008). Evaluating causal effect predictiveness of candidate surrogate endpoints. Biometrics 65, 1223-1232.
-
(2008)
Biometrics
, vol.65
, pp. 1223-1232
-
-
Gilbert, P.B.1
Hudgens, M.G.2
-
12
-
-
15844429309
-
On model expansion, model contraction, identifiability and prior Information: Two illustrative scenarios involving mismeasured variables
-
DOI 10.1214/088342305000000098
-
GUSTAFSON, P. (2005). On model expansion, model contraction, identifability, and prior information: two illustrative scenarios involving mismeasured variables. Statistical Science 20, 111-140. (Pubitemid 41305190)
-
(2005)
Statistical Science
, vol.20
, Issue.2
, pp. 111-140
-
-
Gustafson, P.1
Gelfand, A.E.2
Sahu, S.K.3
Johnson, W.O.4
Hanson, T.E.5
Joseph, L.6
Lee, J.7
-
13
-
-
66949158002
-
Related causal frameworks for surrogate outcomes
-
JOFFE, M. M. AND GREENE, T. (2009). Related causal frameworks for surrogate outcomes. Biometrics 65, 530-538.
-
(2009)
Biometrics
, vol.65
, pp. 530-538
-
-
Joffe, M.M.1
Greene, T.2
-
14
-
-
34548457818
-
Defning and estimating intervention effects for groups that will develop an auxiliary outcome
-
JOFFE, M. M., SMALL, D. AND HSU, C. (2007). Defning and estimating intervention effects for groups that will develop an auxiliary outcome. Statistical Science 22, 74-97.
-
(2007)
Statistical Science
, vol.22
, pp. 74-97
-
-
Joffe, M.M.1
Small, D.2
Hsu, C.3
-
15
-
-
77952987667
-
A Bayesian approach to surrogacy assessment using princi-pal stratifcation in clinical trials
-
LI, Y., TAYLOR, J. M. G. AND ELLIOTT, M. R. (2010). A Bayesian approach to surrogacy assessment using princi-pal stratifcation in clinical trials. Biometrics 66, 523-531.
-
(2010)
Biometrics
, vol.66
, pp. 523-531
-
-
I, Y.L.1
Taylor, J.M.G.2
Elliott, M.R.3
-
16
-
-
0024520844
-
Surrogate endpoints in clinical trials: Definition and operational criteria
-
PRENTICE, R. L. (1989). Surrogate endpoints in clinical trials, defnition and operational criteria. Statistics in Medicine 8,431-440. (Pubitemid 19105891)
-
(1989)
Statistics in Medicine
, vol.8
, Issue.4
, pp. 431-440
-
-
Prentice, R.L.1
-
17
-
-
0002531157
-
Bayesian-inference for causal effects\role ofrandomization
-
RUBIN, D. B. (1978). Bayesian-inference for causal effects\role ofrandomization. The Annals of Statistics 6, 34-58.
-
(1978)
The Annals of Statistics
, vol.6
, pp. 34-58
-
-
Rubin, D.B.1
-
18
-
-
84950657856
-
Randomization analysis of experimental-data-the Fisher randomization test\comment
-
RUBIN, D. B. (1980). Randomization analysis of experimental-data-the Fisher randomization test\comment. Journal of American Statistical Association 75, 591-593.
-
(1980)
Journal of American Statistical Association
, vol.75
, pp. 591-593
-
-
Rubin, D.B.1
-
19
-
-
35648964774
-
End points for colon cancer adjuvant trials: Observations and recommendations based on individual patient data from 20,898 patients enrolled onto 18 randomized trials from the ACCENT group
-
DOI 10.1200/JCO.2006.10.4323
-
SARGENT, D. J., PATIYIL, S., YOTHERS, G. andothers (2007). End points for colon cancer adjuvant trials: obser-vations and recommendations based on individual patient data from 20 898 patients enrolled onto 18 randomized trials from the ACCENT Group. Journal of Clinical Oncolology 25, 4569-4574. (Pubitemid 350035314)
-
(2007)
Journal of Clinical Oncology
, vol.25
, Issue.29
, pp. 4569-4574
-
-
Sargent, D.J.1
Patiyil, S.2
Yothers, G.3
Haller, D.G.4
Gray, R.5
Benedetti, J.6
Buyse, M.7
Labianca, R.8
Seitz, J.F.9
O'Callaghan, C.J.10
Francini, G.11
Grothey, A.12
O'Connell, M.13
Catalano, P.J.14
Kerr, D.15
Green, E.16
Wieand, H.S.17
Goldberg, R.M.18
De Gramont, A.19
-
20
-
-
33644834827
-
Disease-free survival versus overall survival as a primary end point for adjuvant colon cancer studies: Individual patient data from 20,898 patients on 18 randomized trials
-
DOI 10.1200/JCO.2005.01.6071
-
SARGENT, D. J., WIEAND, H. S., HALLER, D. G., andothers (2005). Disease-free survival versus overall survival as a primary end point for adjuvant colon cancer studies: individual patient data from 20 898 patients on 18 randomized trials. Journal of Clinical Oncolology 23, 8664-8670. (Pubitemid 46211509)
-
(2005)
Journal of Clinical Oncology
, vol.23
, Issue.34
, pp. 8664-8670
-
-
Sargent, D.J.1
Wieand, H.S.2
Haller, D.G.3
Gray, R.4
Benedetti, J.K.5
Buyse, M.6
Labianca, R.7
Seitz, J.F.8
O'Callaghan, C.J.9
Francini, G.10
Grothey, A.11
O'Connell, M.12
Catalano, P.J.13
Blanke, C.D.14
Kerr, D.15
Green, E.16
Wolmark, N.17
Andre, T.18
Goldberg, R.M.19
De Gramont, A.20
more..
-
21
-
-
33644859247
-
Counterfactual links to the proportion of treatment effect explained by a surrogate marker
-
DOI 10.1111/j.1541-0420.2005.00380.x
-
TAYLOR, J. M. G., WANG, Y. AND THIÉBAUT, R. (2005). Counterfactual links to the proportion oftreatment effect explained by a surrogate marker. Biometrics 61, 1102-1111. (Pubitemid 43906918)
-
(2005)
Biometrics
, vol.61
, Issue.4
, pp. 1102-1111
-
-
Taylor, J.M.G.1
Wang, Y.2
Thiebaut, R.3
-
22
-
-
40449120916
-
Information theory-based surrogate marker evaluation from several randomized clinical trials with binary endpoints, using SAS
-
DOI 10.1080/10543400701697190, PII 791344031
-
TILAHUN, A., PRYSELEY, A., ALONSO, A. and others (2008). Information theory-based surrogate marker eval-uation from several randomized clinical trials with binary endpoints, using SAS. Journal of Biopharmaceutical Statistics 18, 326-341. (Pubitemid 351355150)
-
(2008)
Journal of Biopharmaceutical Statistics
, vol.18
, Issue.2
, pp. 326-341
-
-
Tilahun, A.1
Pryseley, A.2
Alonso, A.3
Molenberghs, G.4
-
23
-
-
78650039193
-
Statistical identifability and the surrogate endpoint problem, with appli-cation to vaccine trials
-
WOLFSON, J. AND GILBERT, P. (2010). Statistical Identifability and the Surrogate Endpoint Problem, with Appli-cation to Vaccine Trials. Biometrics 66, 1153-1161.
-
(2010)
Biometrics
, vol.66
, pp. 1153-1161
-
-
Wolfson, J.1
Gilbert, P.2
|