-
1
-
-
0033619671
-
Performance of a general location model with an ignorable missing data assumption in a multivariate mental health services study
-
T.R. Belin, M.Y. Hu,A.S.Young, and O. Grusky, Performance of a general location model with an ignorable missing data assumption in a multivariate mental health services study, Statist. Med. 18 (1999), pp. 3123-3135.
-
(1999)
Statist. Med.
, vol.18
, pp. 3123-3135
-
-
Belin, T.R.1
Hu, M.Y.2
Young, A.S.3
Grusky, O.4
-
2
-
-
0035755636
-
A comparison of inclusive and restrictive strategies in modern missing data procedures
-
L.M. Collins, J.L. Schafer, and C.H. Kam, A comparison of inclusive and restrictive strategies in modern missing data procedures, Psychol. Methods 6 (2001), pp. 330-351.
-
(2001)
Psychol. Methods
, vol.6
, pp. 330-351
-
-
Collins, L.M.1
Schafer, J.L.2
Kam, C.H.3
-
3
-
-
10944236293
-
Simulation-driven inferences for multiply imputed longitudinal datasets
-
H. Demirtas, Simulation-driven inferences for multiply imputed longitudinal datasets, Statist. Neerlandica 58 (2004), pp. 466-482.
-
(2004)
Statist. Neerlandica
, vol.58
, pp. 466-482
-
-
Demirtas, H.1
-
4
-
-
18744401063
-
Bayesian analysis of hierarchical pattern-mixture models for clinical trials data with attrition and comparisons to commonly used ad-hoc and model-based approaches
-
H. Demirtas, Bayesian analysis of hierarchical pattern-mixture models for clinical trials data with attrition and comparisons to commonly used ad-hoc and model-based approaches, J. Biopharmaceut. Statist. 25 (2005), pp. 383-402.
-
(2005)
J. Biopharmaceut. Statist.
, vol.25
, pp. 383-402
-
-
Demirtas, H.1
-
5
-
-
23244447184
-
Multiple imputation under Bayesianly smoothed pattern-mixture models for non-ignorable drop-out
-
H. Demirtas, Multiple imputation under Bayesianly smoothed pattern-mixture models for non-ignorable drop-out, Statist. Med. 24 (2005), pp. 2345-2363.
-
(2005)
Statist. Med.
, vol.24
, pp. 2345-2363
-
-
Demirtas, H.1
-
6
-
-
34547471668
-
Practical advice on how to impute continuous data when the ultimate interest centers on dichotomized outcomes through pre-specified thresholds
-
H. Demirtas, Practical advice on how to impute continuous data when the ultimate interest centers on dichotomized outcomes through pre-specified thresholds, Commun. Statist.-Simulation Comput. 36 (2007), pp. 871-889.
-
(2007)
Commun. Statist.-Simulation Comput.
, vol.36
, pp. 871-889
-
-
Demirtas, H.1
-
7
-
-
33846837287
-
Gaussianization-based quasi-imputation and expansion strategies for incomplete correlated binary responses
-
H. Demirtas and D. Hedeker, Gaussianization-based quasi-imputation and expansion strategies for incomplete correlated binary responses, Statist. Med. 26 (2007), pp. 782-799.
-
(2007)
Statist. Med.
, vol.26
, pp. 782-799
-
-
Demirtas, H.1
Hedeker, D.2
-
8
-
-
0042066687
-
On the performance of random-coefficient pattern-mixture models for non-ignorable drop-out
-
H. Demirtas and J.L. Schafer, On the performance of random-coefficient pattern-mixture models for non-ignorable drop-out, Statist. Med. 22 (2003), pp. 2253-2575.
-
(2003)
Statist. Med.
, vol.22
, pp. 2253-2575
-
-
Demirtas, H.1
Schafer, J.L.2
-
9
-
-
33947702607
-
On the performance of bias-reduction techniques for variance estimation in approximate Bayesian bootstrap imputation
-
H. Demirtas, L.M. Arguelles, H. Chung, and D. Hedeker, On the performance of bias-reduction techniques for variance estimation in approximate Bayesian bootstrap imputation, Comput. Statist. Data Anal. 51 (2007), pp. 4064-4068.
-
(2007)
Comput. Statist. Data Anal.
, vol.51
, pp. 4064-4068
-
-
Demirtas, H.1
Arguelles, L.M.2
Chung, H.3
Hedeker, D.4
-
10
-
-
38349186156
-
Plausibility of multivariate normality assumption when multiply imputing non-Gaussian continuous outcomes: A simulation assessment
-
H. Demirtas, S.A. Freels, and R.M. Yucel, Plausibility of multivariate normality assumption when multiply imputing non-Gaussian continuous outcomes: A simulation assessment, J. Statist. Comput. Simulation 78 (2008), pp. 69-84.
-
(2008)
J. Statist. Comput. Simulation
, vol.78
, pp. 69-84
-
-
Demirtas, H.1
Freels, S.A.2
Yucel, R.M.3
-
11
-
-
34250686456
-
Multiple imputation: Review of theory, implementation and software
-
O. Harel and X.H. Zhou, Multiple imputation: review of theory, implementation and software, Statist. Med. 26 (2007), pp. 3057-3077.
-
(2007)
Statist. Med.
, vol.26
, pp. 3057-3077
-
-
Harel, O.1
Zhou, X.H.2
-
12
-
-
0028650772
-
A random-effects ordinal regression model for multilevel analysis
-
D. Hedeker and R.D. Gibbons, A random-effects ordinal regression model for multilevel analysis, Biometrics 50 (1994), pp. 933-944.
-
(1994)
Biometrics
, vol.50
, pp. 933-944
-
-
Hedeker, D.1
Gibbons, R.D.2
-
13
-
-
0002105479
-
Application of random effects pattern-mixture models for missing data in longitudinal studies
-
D. Hedeker and R.D. Gibbons, Application of random effects pattern-mixture models for missing data in longitudinal studies, Psychol. Methods 2 (1997), pp. 64-78.
-
(1997)
Psychol. Methods
, vol.2
, pp. 64-78
-
-
Hedeker, D.1
Gibbons, R.D.2
-
14
-
-
33846873244
-
Much ado about nothing: A comparison of missing data methods and software to fit incomplete data regression models
-
N.J. Horton and K.P. Kleinman, Much ado about nothing: A comparison of missing data methods and software to fit incomplete data regression models, Amer. Statist. 61 (2007), pp. 79-90.
-
(2007)
Amer. Statist.
, vol.61
, pp. 79-90
-
-
Horton, N.J.1
Kleinman, K.P.2
-
15
-
-
0242710940
-
A potential bias when rounding in multiple imputation
-
N.J. Horton, S.R. Lipsitz, and M. Parzen, A potential bias when rounding in multiple imputation, Amer. Statist. 57 (2003), pp. 229-232.
-
(2003)
Amer. Statist.
, vol.57
, pp. 229-232
-
-
Horton, N.J.1
Lipsitz, S.R.2
Parzen, M.3
-
16
-
-
0020333131
-
Random-effects models for longitudinal data
-
N.M. Laird and J.H. Ware, Random-effects models for longitudinal data, Biometrics 38 (1982), pp. 963-974.
-
(1982)
Biometrics
, vol.38
, pp. 963-974
-
-
Laird, N.M.1
Ware, J.H.2
-
18
-
-
0000317187
-
Multivariate correlation models with mixed discrete and continuous variables
-
I. Olkin and R.F. Tate, Multivariate correlation models with mixed discrete and continuous variables, Ann. Math. Statist., 32 (1961), pp. 448-465.
-
(1961)
Ann. Math. Statist.
, vol.32
, pp. 448-465
-
-
Olkin, I.1
Tate, R.F.2
-
20
-
-
0017133178
-
Inference and missing data
-
D.B. Rubin, Inference and missing data, Biometrika 21 (1976), pp. 581-592.
-
(1976)
Biometrika
, vol.21
, pp. 581-592
-
-
Rubin, D.B.1
-
21
-
-
0030539070
-
Multiple imputation after 18+ years (with discussion)
-
D.B. Rubin, Multiple imputation after 18+ years (with discussion), J.Amer. Statist.Assoc. 91 (1996), pp. 473-520.
-
(1996)
J. Amer. Statist. Assoc.
, vol.91
, pp. 473-520
-
-
Rubin, D.B.1
-
24
-
-
0032960273
-
Multiple imputation: A primer
-
J.L. Schafer, Multiple imputation: a primer, Statist. Methods Med. Res. 8 (1999), pp. 3-15.
-
(1999)
Statist. Methods Med. Res.
, vol.8
, pp. 3-15
-
-
Schafer, J.L.1
-
25
-
-
0003742458
-
-
Data Analysis Products Division, Insightful Corp., Seattle, WA
-
J. Schimert, J.L. Schafer, T. Hesterberg, C. Fraley, and D.B. Clarkson, Analyzing Data with MissingValues in S-plus, Data Analysis Products Division, Insightful Corp., Seattle, WA, 2001.
-
(2001)
Analyzing Data With Missingvalues In S-plus
-
-
Schimert, J.1
Schafer, J.L.2
Hesterberg, T.3
Fraley, C.4
Clarkson, D.B.5
-
26
-
-
34347407592
-
Multiple imputation of discrete and continuous data by fully conditional specification
-
S. van Buuren, Multiple imputation of discrete and continuous data by fully conditional specification, Statist. Meth. Med. Res. 16 (2007), pp. 219-242.
-
(2007)
Statist. Meth. Med. Res.
, vol.16
, pp. 219-242
-
-
van Buuren, S.1
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