-
2
-
-
33748520872
-
Review: a gentle introduction to imputation of missing values
-
Donders ART, van der Heijden GJ, Stijnen T, Moons KG. Review: a gentle introduction to imputation of missing values. Journal of Clinical Epidemiology 2006; 59(10): 1087–1091.
-
(2006)
Journal of Clinical Epidemiology
, vol.59
, Issue.10
, pp. 1087-1091
-
-
Donders, A.R.T.1
van der Heijden, G.J.2
Stijnen, T.3
Moons, K.G.4
-
3
-
-
77952419524
-
Missing covariate data in medical research: to impute is better than to ignore
-
Janssen KJ, Donders ART, Harrell FE Jr., Vergouwe Y, Chen Q, Grobbee DE, Moons KG. Missing covariate data in medical research: to impute is better than to ignore. Journal of Clinical Epidemiology 2010; 63(7): 721–727.
-
(2010)
Journal of Clinical Epidemiology
, vol.63
, Issue.7
, pp. 721-727
-
-
Janssen, K.J.1
Donders, A.R.T.2
Harrell, F.E.3
Vergouwe, Y.4
Chen, Q.5
Grobbee, D.E.6
Moons, K.G.7
-
4
-
-
77952422361
-
Unpredictable bias when using the missing indicator method or complete case analysis for missing confounder values: an empirical example
-
Knol MJ, Janssen KJ, Donders ART, Egberts AC, Heerdink ER, Grobbee DE, Moons KG, Geerlings MI. Unpredictable bias when using the missing indicator method or complete case analysis for missing confounder values: an empirical example. Journal of Clinical Epidemiology 2010; 63(7): 728–736.
-
(2010)
Journal of Clinical Epidemiology
, vol.63
, Issue.7
, pp. 728-736
-
-
Knol, M.J.1
Janssen, K.J.2
Donders, A.R.T.3
Egberts, A.C.4
Heerdink, E.R.5
Grobbee, D.E.6
Moons, K.G.7
Geerlings, M.I.8
-
5
-
-
68249114452
-
Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls
-
Sterne JA, White IR, Carlin JB, Spratt M, Royston P, Kenward MG, Wood AM, Carpenter JR. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ (Clinical research ed.) 2009; 338:b2393: 157–160.
-
(2009)
BMJ (Clinical research ed.)
, vol.338:b2393
, pp. 157-160
-
-
Sterne, J.A.1
White, I.R.2
Carlin, J.B.3
Spratt, M.4
Royston, P.5
Kenward, M.G.6
Wood, A.M.7
Carpenter, J.R.8
-
6
-
-
84977483937
-
Flexible Imputation of Missing Data, Chapman & Hall/CRC Interdisciplinary Statistics
-
Boca Raton, FL
-
van Buuren S. Flexible Imputation of Missing Data, Chapman & Hall/CRC Interdisciplinary Statistics. CRC Press Taylor & Francis Group: Boca Raton, FL, 2012.
-
(2012)
CRC Press Taylor & Francis Group
-
-
van Buuren, S.1
-
8
-
-
33748709502
-
Using the outcome for imputation of missing predictor values was preferred
-
Moons KG, Donders RA, Stijnen T, Harrell FE Jr. Using the outcome for imputation of missing predictor values was preferred. Journal of Clinical Epidemiology 2006; 59(10): 1092–1101.
-
(2006)
Journal of Clinical Epidemiology
, vol.59
, Issue.10
, pp. 1092-1101
-
-
Moons, K.G.1
Donders, R.A.2
Stijnen, T.3
Harrell, F.E.4
-
10
-
-
63049094081
-
Multilevel models with multivariate mixed response types
-
Goldstein H, Carpenter J, Kenward MG, Levin KA. Multilevel models with multivariate mixed response types. Statistical Modelling 2009; 9(3): 173–197.
-
(2009)
Statistical Modelling
, vol.9
, Issue.3
, pp. 173-197
-
-
Goldstein, H.1
Carpenter, J.2
Kenward, M.G.3
Levin, K.A.4
-
11
-
-
0036016749
-
Bayesian methods for generalized linear models with covariates missing at random
-
Ibrahim JG, Chen M-H, Lipsitz SR. Bayesian methods for generalized linear models with covariates missing at random. Canadian Journal of Statistics 2002; 30(1): 55–78.
-
(2002)
Canadian Journal of Statistics
, vol.30
, Issue.1
, pp. 55-78
-
-
Ibrahim, J.G.1
Chen, M.-H.2
Lipsitz, S.R.3
-
12
-
-
0346102882
-
Maximum likelihood methods for nonignorable missing responses and covariates in random effects models
-
Stubbendick AL, Ibrahim JG. Maximum likelihood methods for nonignorable missing responses and covariates in random effects models. Biometrics 2003; 59(4): 1140–1150.
-
(2003)
Biometrics
, vol.59
, Issue.4
, pp. 1140-1150
-
-
Stubbendick, A.L.1
Ibrahim, J.G.2
-
13
-
-
77952557371
-
Weighted generalized estimating functions for longitudinal response and covariate data that are missing at random
-
Chen B, Grace YY, Cook RJ. Weighted generalized estimating functions for longitudinal response and covariate data that are missing at random. Journal of the American Statistical Association 2010; 105(489): 336–353.
-
(2010)
Journal of the American Statistical Association
, vol.105
, Issue.489
, pp. 336-353
-
-
Chen, B.1
Grace, Y.Y.2
Cook, R.J.3
-
14
-
-
80052808295
-
Doubly robust estimates for binary longitudinal data analysis with missing response and missing covariates
-
Chen B, Zhou XH. Doubly robust estimates for binary longitudinal data analysis with missing response and missing covariates. Biometrics 2011; 67(3): 830–842.
-
(2011)
Biometrics
, vol.67
, Issue.3
, pp. 830-842
-
-
Chen, B.1
Zhou, X.H.2
-
15
-
-
84871337994
-
The Generation R study: design and cohort update 2012
-
Jaddoe VW, van Duijn CM, Franco OH, van der Heijden AJ, van IIzendoorn MH, de Jongste JC, van der Lugt A, Mackenbach JP, Moll HA, Raat, H, Rivadeneira F, Steegers EA, Tiemeier H, Uitterlinden AG, Verhulst FC, Hofman A. The Generation R study: design and cohort update 2012. European Journal of Epidemiology 2012; 27(9): 739–756.
-
(2012)
European Journal of Epidemiology
, vol.27
, Issue.9
, pp. 739-756
-
-
Jaddoe, V.W.1
van Duijn, C.M.2
Franco, O.H.3
van der Heijden, A.J.4
van IIzendoorn, M.H.5
de Jongste, J.C.6
van der Lugt, A.7
Mackenbach, J.P.8
Moll, H.A.9
Raat, H.10
Rivadeneira, F.11
Steegers, E.A.12
Tiemeier, H.13
Uitterlinden, A.G.14
Verhulst, F.C.15
Hofman, A.16
-
16
-
-
0003496949
-
-
John Wiley & Sons, Inc., Hoboken, New Jersey
-
Little R, Rubin D. Statistical Analysis with Missing Data, Wiley Series in Probability and Statistics - Applied Probability and Statistics Section Series. John Wiley & Sons, Inc.: Hoboken, New Jersey, 1987.
-
(1987)
Statistical Analysis with Missing Data, Wiley Series in Probability and Statistics - Applied Probability and Statistics Section Series
-
-
Little, R.1
Rubin, D.2
-
17
-
-
84878958480
-
What is meant by “missing at random”?
-
Seaman S, Galati J, Jackson D, Carlin J. What is meant by “missing at random”?Statistical Science 2013; 28(2): 257–268.
-
(2013)
Statistical Science
, vol.28
, Issue.2
, pp. 257-268
-
-
Seaman, S.1
Galati, J.2
Jackson, D.3
Carlin, J.4
-
19
-
-
84937894556
-
Multiple imputation of covariates by fully conditional specification: accommodating the substantive model
-
Bartlett JW, Seaman SR, White IR, Carpenter JR. Multiple imputation of covariates by fully conditional specification: accommodating the substantive model. Statistical Methods in Medical Research 2015; 24(4): 462–487.
-
(2015)
Statistical Methods in Medical Research
, vol.24
, Issue.4
, pp. 462-487
-
-
Bartlett, J.W.1
Seaman, S.R.2
White, I.R.3
Carpenter, J.R.4
-
20
-
-
0035102205
-
Maximum likelihood methods for cure rate models with missing covariates
-
Chen M-H, Ibrahim JG. Maximum likelihood methods for cure rate models with missing covariates. Biometrics 2001; 57(1): 43–52.
-
(2001)
Biometrics
, vol.57
, Issue.1
, pp. 43-52
-
-
Chen, M.-H.1
Ibrahim, J.G.2
-
21
-
-
84977491683
-
Analysis of Incomplete Multivariate Data, Chapman & Hall/CRC Monographs on Statistics & Applied Probability
-
Boca Raton, FL
-
Schafer J. Analysis of Incomplete Multivariate Data, Chapman & Hall/CRC Monographs on Statistics & Applied Probability. CRC Press Taylor & Francis Group: Boca Raton, FL, 1997.
-
(1997)
CRC Press Taylor & Francis Group
-
-
Schafer, J.1
-
22
-
-
84946962849
-
Convergence properties of a sequential regression multiple imputation algorithm
-
Zhu J, Raghunathan TE. Convergence properties of a sequential regression multiple imputation algorithm. Journal of the American Statistical Association 2015; 110(511): 1112–1124.
-
(2015)
Journal of the American Statistical Association
, vol.110
, Issue.511
, pp. 1112-1124
-
-
Zhu, J.1
Raghunathan, T.E.2
-
23
-
-
84943645306
-
Fitting linear mixed-effects models using lme4
-
Bates D, Mächler M, Bolker B, Walker S. Fitting linear mixed-effects models using lme4. Journal of Statistical Software 2015; 67(1): 1–48.
-
(2015)
Journal of Statistical Software
, vol.67
, Issue.1
, pp. 1-48
-
-
Bates, D.1
Mächler, M.2
Bolker, B.3
Walker, S.4
-
24
-
-
84907095419
-
R: A Language and Environment for Statistical Computing
-
Vienna, Austria
-
R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing: Vienna, Austria, 2013. http://www.R-project.org/.
-
(2013)
R Foundation for Statistical Computing
-
-
-
25
-
-
67650521193
-
JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling
-
In, Hornik K., Leisch F., Zeileis A., (eds), Vienna, Austria
-
Plummer M. 2003. JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling. In Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003), Hornik K., Leisch F., Zeileis A. (eds): Vienna, Austria.
-
(2003)
Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003)
-
-
Plummer, M.1
-
26
-
-
0033636097
-
Latent class model diagnosis
-
Garrett ES, Zeger SL. Latent class model diagnosis. Biometrics 2000; 56(4): 1055–1067.
-
(2000)
Biometrics
, vol.56
, Issue.4
, pp. 1055-1067
-
-
Garrett, E.S.1
Zeger, S.L.2
-
27
-
-
25444484077
-
Posterior predictive assessment of model fitness via realized discrepancies
-
Gelman A, Meng XL, Stern H. Posterior predictive assessment of model fitness via realized discrepancies. Statistica Sinica 1996; 6(4): 733–760.
-
(1996)
Statistica Sinica
, vol.6
, Issue.4
, pp. 733-760
-
-
Gelman, A.1
Meng, X.L.2
Stern, H.3
-
29
-
-
78651256743
-
Multiple imputation using chained equations: issues and guidance for practice
-
White IR, Royston P, Wood AM. Multiple imputation using chained equations: issues and guidance for practice. Statistics in Medicine 2011; 30(4): 377–399.
-
(2011)
Statistics in Medicine
, vol.30
, Issue.4
, pp. 377-399
-
-
White, I.R.1
Royston, P.2
Wood, A.M.3
-
30
-
-
84856249157
-
State of the multiple imputation software
-
Yucel RM. State of the multiple imputation software. Journal of Statistical Software 2011; 45(1): 1–7.
-
(2011)
Journal of Statistical Software
, vol.45
, Issue.1
, pp. 1-7
-
-
Yucel, R.M.1
-
34
-
-
0006407254
-
WinBUGS-a Bayesian modelling framework: concepts, structure, and extensibility
-
Lunn DJ, Thomas A, Best N, Spiegelhalter D. WinBUGS-a Bayesian modelling framework: concepts, structure, and extensibility. Statistics and Computing 2000; 10(4): 325–337.
-
(2000)
Statistics and Computing
, vol.10
, Issue.4
, pp. 325-337
-
-
Lunn, D.J.1
Thomas, A.2
Best, N.3
Spiegelhalter, D.4
|