-
1
-
-
14144252238
-
A random effects transition model for longitudinal binary data with informative missingness
-
Albert P., and Follman D. A random effects transition model for longitudinal binary data with informative missingness. Statist. Neerlandica 57 (2003) 100-111
-
(2003)
Statist. Neerlandica
, vol.57
, pp. 100-111
-
-
Albert, P.1
Follman, D.2
-
3
-
-
34547901089
-
-
Best, N., Cowles, M., Vines, S., 1995. Coda: convergence diagnosis and output analysis software for Gibbs sampling output. Technical Report, MRC Biostatistics Unit, Cambridge.
-
-
-
-
4
-
-
0032273615
-
General methods for monitoring convergence of iterative simulations
-
Brooks S.P., and Gelman A. General methods for monitoring convergence of iterative simulations. J. Comput. Graphical Statist. 7 (1998) 434-455
-
(1998)
J. Comput. Graphical Statist.
, vol.7
, pp. 434-455
-
-
Brooks, S.P.1
Gelman, A.2
-
5
-
-
0037197598
-
Coping with missing data in clinical trials: a model-based approach applied to asthma trials
-
Carpenter J., Pocock S., and Lamm C.J. Coping with missing data in clinical trials: a model-based approach applied to asthma trials. Statist. Med. 21 (2002) 1043-1066
-
(2002)
Statist. Med.
, vol.21
, pp. 1043-1066
-
-
Carpenter, J.1
Pocock, S.2
Lamm, C.J.3
-
7
-
-
0033064099
-
High-dose (HI-DPA) vs low-dose (LO-DPA) penicillamine in early diffuse systemic sclerosis (SSc) trial: analysis of a two-year, double-blind, randomized, controlled clinical trial
-
Clements P., Furst D., Wong W., Mayes M., White B., Wigley F., Weisman M., Barr W., Moreland L., Medsger T., Steen Jr. V., Martin R., Collier D., Weinstein A., Lally E., Varga J., Weiner S., Andrews B., Abeles M., and Seibold J. High-dose (HI-DPA) vs low-dose (LO-DPA) penicillamine in early diffuse systemic sclerosis (SSc) trial: analysis of a two-year, double-blind, randomized, controlled clinical trial. Arthritis Rheumatism 42 (1999) 1194-1203
-
(1999)
Arthritis Rheumatism
, vol.42
, pp. 1194-1203
-
-
Clements, P.1
Furst, D.2
Wong, W.3
Mayes, M.4
White, B.5
Wigley, F.6
Weisman, M.7
Barr, W.8
Moreland, L.9
Medsger, T.10
Steen Jr., V.11
Martin, R.12
Collier, D.13
Weinstein, A.14
Lally, E.15
Varga, J.16
Weiner, S.17
Andrews, B.18
Abeles, M.19
Seibold, J.20
more..
-
8
-
-
0033636008
-
Reparameterizing the pattern-mixture model for sensitivity analysis under informative dropout
-
Daniels M., and Hogan J. Reparameterizing the pattern-mixture model for sensitivity analysis under informative dropout. Biometrics 56 (2000) 1241-1248
-
(2000)
Biometrics
, vol.56
, pp. 1241-1248
-
-
Daniels, M.1
Hogan, J.2
-
10
-
-
0028627762
-
Modeling the relationship between disease progression and survival time
-
De Gruttola V., and Tu X. Modeling the relationship between disease progression and survival time. Biometrics 50 (1994) 1003-1014
-
(1994)
Biometrics
, vol.50
, pp. 1003-1014
-
-
De Gruttola, V.1
Tu, X.2
-
11
-
-
0042066687
-
On the performance of rancom-coefficient pattern-mixture models for non-ignorable drop-out
-
Demirtas H., and Schafer J. On the performance of rancom-coefficient pattern-mixture models for non-ignorable drop-out. Statist. Med. 2 (2003) 2553-2575
-
(2003)
Statist. Med.
, vol.2
, pp. 2553-2575
-
-
Demirtas, H.1
Schafer, J.2
-
13
-
-
4243828610
-
Informative drop-out in longitudinal data analysis
-
Diggle P., and Kenward M.G. Informative drop-out in longitudinal data analysis. Appl. Statist. 43 (1994) 49-73
-
(1994)
Appl. Statist.
, vol.43
, pp. 49-73
-
-
Diggle, P.1
Kenward, M.G.2
-
14
-
-
0347363890
-
Diagnostics for joint longitudinal and dropout time modeling
-
Dobson A., and Henderson R. Diagnostics for joint longitudinal and dropout time modeling. Biometrics 59 (2003) 741-751
-
(2003)
Biometrics
, vol.59
, pp. 741-751
-
-
Dobson, A.1
Henderson, R.2
-
15
-
-
34547888374
-
-
Draper, D., Krnjajic, M., 2005. Bayesian model specification. Technical Report, University of California, Santa Cruz.
-
-
-
-
16
-
-
0035044722
-
An alternative parameterization of the general linear mixture model for longitudinal data with non-ignorable dropouts
-
Fitzmaurice G., and Laird N. An alternative parameterization of the general linear mixture model for longitudinal data with non-ignorable dropouts. Statist. Med. 20 (2001) 1009-1021
-
(2001)
Statist. Med.
, vol.20
, pp. 1009-1021
-
-
Fitzmaurice, G.1
Laird, N.2
-
17
-
-
0029028456
-
An approximate generalized linear model with random effects for informative missing data
-
Follman D., and Wu M. An approximate generalized linear model with random effects for informative missing data. Biometrics 51 (1995) 151-168
-
(1995)
Biometrics
, vol.51
, pp. 151-168
-
-
Follman, D.1
Wu, M.2
-
19
-
-
0001526195
-
A predictive approach to model selection
-
Geisser S., and Eddy W. A predictive approach to model selection. J. Amer. Statist. Assoc. 74 (1979) 153-160
-
(1979)
J. Amer. Statist. Assoc.
, vol.74
, pp. 153-160
-
-
Geisser, S.1
Eddy, W.2
-
20
-
-
0000539315
-
Bayesian model choice: asymptotics and exact calculations
-
Gelfand A.E., and Dey D.K. Bayesian model choice: asymptotics and exact calculations. J. Roy. Statist. Soc. Ser. B 56 (1994) 501-514
-
(1994)
J. Roy. Statist. Soc. Ser. B
, vol.56
, pp. 501-514
-
-
Gelfand, A.E.1
Dey, D.K.2
-
21
-
-
84867086419
-
Prior distributions for variance parameters in hierarchical models
-
Gelman A. Prior distributions for variance parameters in hierarchical models. Bayesian Anal. 1 (2006) 515-533
-
(2006)
Bayesian Anal.
, vol.1
, pp. 515-533
-
-
Gelman, A.1
-
22
-
-
84972492387
-
Inference from iterative simulation using multiple sequences (with discussion)
-
Gelman A., and Rubin D.B. Inference from iterative simulation using multiple sequences (with discussion). Statist. Sci. 7 (1992) 457-511
-
(1992)
Statist. Sci.
, vol.7
, pp. 457-511
-
-
Gelman, A.1
Rubin, D.B.2
-
23
-
-
0004012196
-
-
Chapman & Hall, London
-
Gelman A., Carlin J., Stern H., and Rubin D. Bayesian Data Analysis. second ed (2003), Chapman & Hall, London
-
(2003)
Bayesian Data Analysis. second ed
-
-
Gelman, A.1
Carlin, J.2
Stern, H.3
Rubin, D.4
-
26
-
-
10844288743
-
A random pattern-mixture model for longitudinal data with dropouts
-
Guo W., Ratcliffe S., and Ten Have T. A random pattern-mixture model for longitudinal data with dropouts. J. Amer. Statist. Assoc. 99 (2004) 929-937
-
(2004)
J. Amer. Statist. Assoc.
, vol.99
, pp. 929-937
-
-
Guo, W.1
Ratcliffe, S.2
Ten Have, T.3
-
27
-
-
0002105479
-
Application of random-effects pattern-mixture models for missing data in longitudinal studies
-
Hedeker D., and Gibbons R. Application of random-effects pattern-mixture models for missing data in longitudinal studies. Psychol. Methods 2 (1997) 64-78
-
(1997)
Psychol. Methods
, vol.2
, pp. 64-78
-
-
Hedeker, D.1
Gibbons, R.2
-
28
-
-
0037507563
-
Missing responses in generalised linear mixed models when the missingness mechanism is nonignorable
-
Ibrahim J., Chen M.-H., and Lipsitz S. Missing responses in generalised linear mixed models when the missingness mechanism is nonignorable. Biometrika 88 (2001) 551-564
-
(2001)
Biometrika
, vol.88
, pp. 551-564
-
-
Ibrahim, J.1
Chen, M.-H.2
Lipsitz, S.3
-
29
-
-
0032534724
-
Selection models for repeated measurements with non-random dropout: an illustration of sensitivity
-
Kenward M.G. Selection models for repeated measurements with non-random dropout: an illustration of sensitivity. Statist. Med. 17 (1998) 2723-2732
-
(1998)
Statist. Med.
, vol.17
, pp. 2723-2732
-
-
Kenward, M.G.1
-
30
-
-
0020333131
-
Random effects models for longitudinal data
-
Laird N.M., and Ware J.H. Random effects models for longitudinal data. Biometrics 38 (1982) 963-974
-
(1982)
Biometrics
, vol.38
, pp. 963-974
-
-
Laird, N.M.1
Ware, J.H.2
-
31
-
-
2942677478
-
Modeling longitudinal data with nonignorable dropouts using a latent dropout class model
-
Lin H., McCuloch C., and Rosenheck R. Modeling longitudinal data with nonignorable dropouts using a latent dropout class model. Biometrics 60 (2004) 295-305
-
(2004)
Biometrics
, vol.60
, pp. 295-305
-
-
Lin, H.1
McCuloch, C.2
Rosenheck, R.3
-
32
-
-
21144483152
-
Pattern-mixture models for multivariate incomplete data
-
Little R. Pattern-mixture models for multivariate incomplete data. J. Amer. Statist. Assoc. 88 (1993) 125-134
-
(1993)
J. Amer. Statist. Assoc.
, vol.88
, pp. 125-134
-
-
Little, R.1
-
33
-
-
84950452119
-
Modeling the drop-out mechanism in repeated-measures studies
-
Little R. Modeling the drop-out mechanism in repeated-measures studies. J. Amer. Statist. Assoc. 90 (1995) 1112-1121
-
(1995)
J. Amer. Statist. Assoc.
, vol.90
, pp. 1112-1121
-
-
Little, R.1
-
35
-
-
0037197628
-
Selection models and pattern-mixture models to analyse longitudinal quality of life data subject to drop-out
-
Michiels B., Molenberghs G., Bijnens L., Vangeneugden T., and Thijs H. Selection models and pattern-mixture models to analyse longitudinal quality of life data subject to drop-out. Statist. Med. 21 (2002) 1023-1041
-
(2002)
Statist. Med.
, vol.21
, pp. 1023-1041
-
-
Michiels, B.1
Molenberghs, G.2
Bijnens, L.3
Vangeneugden, T.4
Thijs, H.5
-
36
-
-
1842780226
-
Sensitivity analysis of longitudinal normal data with drop-outs
-
Minini P., and Chavance M. Sensitivity analysis of longitudinal normal data with drop-outs. Statist. Med. 23 (2004) 1039-1054
-
(2004)
Statist. Med.
, vol.23
, pp. 1039-1054
-
-
Minini, P.1
Chavance, M.2
-
37
-
-
28444468503
-
Sensitivity analysis of continous incomplete longitudinal outcomes
-
Molenberghs G., and Thijs H. Sensitivity analysis of continous incomplete longitudinal outcomes. Statist. Neerlandica 57 (2003) 112-135
-
(2003)
Statist. Neerlandica
, vol.57
, pp. 112-135
-
-
Molenberghs, G.1
Thijs, H.2
-
38
-
-
0035963906
-
Influence analysis to assess sensitivity of dropout process
-
Molenberghs G., Verbeke G., Thijs H., Lesaffre E., and Kenward M. Influence analysis to assess sensitivity of dropout process. Comput. Statist. Data Anal. 37 (2001) 93-113
-
(2001)
Comput. Statist. Data Anal.
, vol.37
, pp. 93-113
-
-
Molenberghs, G.1
Verbeke, G.2
Thijs, H.3
Lesaffre, E.4
Kenward, M.5
-
40
-
-
0346733311
-
Modeling longitudinal data with nonignorable dropouts using a latent dropout class model
-
Roy J. Modeling longitudinal data with nonignorable dropouts using a latent dropout class model. Biostatistics 59 (2003) 829-836
-
(2003)
Biostatistics
, vol.59
, pp. 829-836
-
-
Roy, J.1
-
42
-
-
2942658011
-
Incorporating prior beliefs about selection bias into the analysis of randomized trials with missing outcomes
-
Scharfstein D.O., Daniels M.J., and Robins J.M. Incorporating prior beliefs about selection bias into the analysis of randomized trials with missing outcomes. Biostatistics 4 (2003) 495-512
-
(2003)
Biostatistics
, vol.4
, pp. 495-512
-
-
Scharfstein, D.O.1
Daniels, M.J.2
Robins, J.M.3
-
43
-
-
0003470083
-
-
MRC Biostatistics Unit, Cambridge
-
Spiegelhalter D., Thomas A., Best N., and Gilks W. BUGS: Bayesian Inference Using Gibbs Sampling (1995), MRC Biostatistics Unit, Cambridge
-
(1995)
BUGS: Bayesian Inference Using Gibbs Sampling
-
-
Spiegelhalter, D.1
Thomas, A.2
Best, N.3
Gilks, W.4
-
47
-
-
0031944647
-
Mixed effects logistic regression models for longitudinal binary response data with informative drop-out
-
Ten Have T., Kunselman A., Pulkstenis E., and Landis J. Mixed effects logistic regression models for longitudinal binary response data with informative drop-out. Biometrics 54 (1998) 367-383
-
(1998)
Biometrics
, vol.54
, pp. 367-383
-
-
Ten Have, T.1
Kunselman, A.2
Pulkstenis, E.3
Landis, J.4
-
48
-
-
0042487265
-
Strategies to fit pattern-mixture models
-
Thijs H., Molenberghs G., Verbeke G., Michiels B., and Curran D. Strategies to fit pattern-mixture models. Biostatistics 3 (2002) 245-266
-
(2002)
Biostatistics
, vol.3
, pp. 245-266
-
-
Thijs, H.1
Molenberghs, G.2
Verbeke, G.3
Michiels, B.4
Curran, D.5
-
49
-
-
0039982650
-
Analysis of longitudinal data with non-ignorable non-monotone missing values
-
Troxel A., Harrington D., and Lipsitz S. Analysis of longitudinal data with non-ignorable non-monotone missing values. Appl. Statist. 47 (1998) 425-438
-
(1998)
Appl. Statist.
, vol.47
, pp. 425-438
-
-
Troxel, A.1
Harrington, D.2
Lipsitz, S.3
-
51
-
-
0023779040
-
Analysis changes in the presence of informative right censoring caused by death and withdrawal
-
Wu M., and Bailey K. Analysis changes in the presence of informative right censoring caused by death and withdrawal. Statist. Med. 7 (1988) 337-346
-
(1988)
Statist. Med.
, vol.7
, pp. 337-346
-
-
Wu, M.1
Bailey, K.2
-
52
-
-
0023921412
-
Estimation and comparison of changes in the presence of informative right censoring by modeling the censoring process
-
Wu M., and Carroll R. Estimation and comparison of changes in the presence of informative right censoring by modeling the censoring process. Biometrics 82 (1988) 175-188
-
(1988)
Biometrics
, vol.82
, pp. 175-188
-
-
Wu, M.1
Carroll, R.2
|