These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

192 related articles for article (PubMed ID: 21155748)

  • 1. A bivariate pseudolikelihood for incomplete longitudinal binary data with nonignorable nonmonotone missingness.
    Sinha SK; Troxel AB; Lipsitz SR; Sinha D; Fitzmaurice GM; Molenberghs G; Ibrahim JG
    Biometrics; 2011 Sep; 67(3):1119-26. PubMed ID: 21155748
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A weighted combination of pseudo-likelihood estimators for longitudinal binary data subject to non-ignorable non-monotone missingness.
    Troxel AB; Lipsitz SR; Fitzmaurice GM; Ibrahim JG; Sinha D; Molenberghs G
    Stat Med; 2010 Jun; 29(14):1511-21. PubMed ID: 20205269
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Adjusting for nonignorable missingness when estimating generalized additive models.
    Xie H
    Biom J; 2010 Apr; 52(2):186-200. PubMed ID: 20422637
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A Two-Step Approach for Analysis of Nonignorable Missing Outcomes in Longitudinal Regression: an Application to Upstate KIDS Study.
    Liu D; Yeung EH; McLain AC; Xie Y; Buck Louis GM; Sundaram R
    Paediatr Perinat Epidemiol; 2017 Sep; 31(5):468-478. PubMed ID: 28767145
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Nonignorable models for intermittently missing categorical longitudinal responses.
    Tsonaka R; Rizopoulos D; Verbeke G; Lesaffre E
    Biometrics; 2010 Sep; 66(3):834-44. PubMed ID: 19995352
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A semi-parametric shared parameter model to handle nonmonotone nonignorable missingness.
    Tsonaka R; Verbeke G; Lesaffre E
    Biometrics; 2009 Mar; 65(1):81-7. PubMed ID: 18373713
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Pseudo-likelihood methods for longitudinal binary data with non-ignorable missing responses and covariates.
    Parzen M; Lipsitz SR; Fitzmaurice GM; Ibrahim JG; Troxel A
    Stat Med; 2006 Aug; 25(16):2784-96. PubMed ID: 16345018
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Expected estimating equations for missing data, measurement error, and misclassification, with application to longitudinal nonignorable missing data.
    Wang CY; Huang Y; Chao EC; Jeffcoat MK
    Biometrics; 2008 Mar; 64(1):85-95. PubMed ID: 17608787
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Estimation in regression models for longitudinal binary data with outcome-dependent follow-up.
    Fitzmaurice GM; Lipsitz SR; Ibrahim JG; Gelber R; Lipshultz S
    Biostatistics; 2006 Jul; 7(3):469-85. PubMed ID: 16428260
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Maximum likelihood methods for nonignorable missing responses and covariates in random effects models.
    Stubbendick AL; Ibrahim JG
    Biometrics; 2003 Dec; 59(4):1140-50. PubMed ID: 14969495
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Analysis of crossover designs for longitudinal binary data with ignorable and nonignorable dropout.
    Wang X; Chinchilli VM
    Stat Methods Med Res; 2022 Jan; 31(1):119-138. PubMed ID: 34779672
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Bayesian semiparametric nonlinear mixed-effects joint models for data with skewness, missing responses, and measurement errors in covariates.
    Huang Y; Dagne G
    Biometrics; 2012 Sep; 68(3):943-53. PubMed ID: 22150787
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Analysis of matched case-control data in presence of nonignorable missing exposure.
    Sinha S; Maiti T
    Biometrics; 2008 Mar; 64(1):106-14. PubMed ID: 17573865
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Inference for longitudinal data with nonignorable nonmonotone missing responses.
    Sinha SK; Kaushal A; Xiao W
    Comput Stat Data Anal; 2014 Apr; 72():77-91. PubMed ID: 25435599
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Bayesian pattern-mixture models for dropout and intermittently missing data in longitudinal data analysis.
    Blozis SA
    Behav Res Methods; 2024 Mar; 56(3):1953-1967. PubMed ID: 37221346
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Mixtures of varying coefficient models for longitudinal data with discrete or continuous nonignorable dropout.
    Hogan JW; Lin X; Herman B
    Biometrics; 2004 Dec; 60(4):854-64. PubMed ID: 15606405
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Accounting for dropout reason in longitudinal studies with nonignorable dropout.
    Moore CM; MaWhinney S; Forster JE; Carlson NE; Allshouse A; Wang X; Routy JP; Conway B; Connick E
    Stat Methods Med Res; 2017 Aug; 26(4):1854-1866. PubMed ID: 26078357
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A model for adjusting for nonignorable verification bias in estimation of the ROC curve and its area with likelihood-based approach.
    Liu D; Zhou XH
    Biometrics; 2010 Dec; 66(4):1119-28. PubMed ID: 20222937
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Estimation methods for marginal and association parameters for longitudinal binary data with nonignorable missing observations.
    Li H; Yi GY
    Stat Med; 2013 Feb; 32(5):833-48. PubMed ID: 22833460
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Treatment comparison in randomized clinical trials with nonignorable missingness: A reverse regression approach.
    Zhang Z; Cheon K
    Stat Methods Med Res; 2017 Apr; 26(2):776-795. PubMed ID: 25411324
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.