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 *

219 related articles for article (PubMed ID: 23845158)

  • 1. Shrinkage empirical likelihood estimator in longitudinal analysis with time-dependent covariates--application to modeling the health of Filipino children.
    Leung DH; Small DS; Qin J; Zhu M
    Biometrics; 2013 Sep; 69(3):624-32. PubMed ID: 23845158
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Efficient parameter estimation in longitudinal data analysis using a hybrid GEE method.
    Leung DH; Wang YG; Zhu M
    Biostatistics; 2009 Jul; 10(3):436-45. PubMed ID: 19346528
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A caveat concerning independence estimating equations with multivariate binary data.
    Fitzmaurice GM
    Biometrics; 1995 Mar; 51(1):309-17. PubMed ID: 7766784
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Application of generalized estimating equations to a study of in vitro radiation sensitivity.
    Cologne JB; Carter RL; Fujita S; Ban S
    Biometrics; 1993 Sep; 49(3):927-34. PubMed ID: 8241379
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Using modified approaches on marginal regression analysis of longitudinal data with time-dependent covariates.
    Zhou Y; Lefante J; Rice J; Chen S
    Stat Med; 2014 Aug; 33(19):3354-64. PubMed ID: 24723212
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Penalized generalized estimating equations for high-dimensional longitudinal data analysis.
    Wang L; Zhou J; Qu A
    Biometrics; 2012 Jun; 68(2):353-60. PubMed ID: 21955051
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Model selection of generalized estimating equations with multiply imputed longitudinal data.
    Shen CW; Chen YH
    Biom J; 2013 Nov; 55(6):899-911. PubMed ID: 23970494
    [TBL] [Abstract][Full Text] [Related]  

  • 8. An application of maximum likelihood and generalized estimating equations to the analysis of ordinal data from a longitudinal study with cases missing at random.
    Kenward MG; Lesaffre E; Molenberghs G
    Biometrics; 1994 Dec; 50(4):945-53. PubMed ID: 7787007
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Model selection for generalized estimating equations accommodating dropout missingness.
    Shen CW; Chen YH
    Biometrics; 2012 Dec; 68(4):1046-54. PubMed ID: 22463099
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A weighted estimating equation for linear regression with missing covariate data.
    Parzen M; Lipsitz SR; Ibrahim JG; Lipshultz S
    Stat Med; 2002 Aug; 21(16):2421-36. PubMed ID: 12210626
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Effects of variance-function misspecification in analysis of longitudinal data.
    Wang YG; Lin X
    Biometrics; 2005 Jun; 61(2):413-21. PubMed ID: 16011687
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Comparison of generalized estimating equations and quadratic inference functions using data from the National Longitudinal Survey of Children and Youth (NLSCY) database.
    Odueyungbo A; Browne D; Akhtar-Danesh N; Thabane L
    BMC Med Res Methodol; 2008 May; 8():28. PubMed ID: 18466627
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Generalized estimating equation model for binary outcomes with missing covariates.
    Xie F; Paik MC
    Biometrics; 1997 Dec; 53(4):1458-66. PubMed ID: 9423260
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Analyzing spatially distributed binary data using independent-block estimating equations.
    Oman SD; Landsman V; Carmel Y; Kadmon R
    Biometrics; 2007 Sep; 63(3):892-900. PubMed ID: 17489971
    [TBL] [Abstract][Full Text] [Related]  

  • 15. The analysis of longitudinal polytomous data: generalized estimating equations and connections with weighted least squares.
    Miller ME; Davis CS; Landis JR
    Biometrics; 1993 Dec; 49(4):1033-44. PubMed ID: 8117899
    [TBL] [Abstract][Full Text] [Related]  

  • 16. GEE for multinomial responses using a local odds ratios parameterization.
    Touloumis A; Agresti A; Kateri M
    Biometrics; 2013 Sep; 69(3):633-40. PubMed ID: 23724948
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Improved methods for the marginal analysis of longitudinal data in the presence of time-dependent covariates.
    Chen IC; Westgate PM
    Stat Med; 2017 Jul; 36(16):2533-2546. PubMed ID: 28436045
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A note on the use of unbiased estimating equations to estimate correlation in analysis of longitudinal trials.
    Sun W; Shults J; Leonard M
    Biom J; 2009 Feb; 51(1):5-18. PubMed ID: 19197953
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Correlation structure and variable selection in generalized estimating equations via composite likelihood information criteria.
    Nikoloulopoulos AK
    Stat Med; 2016 Jun; 35(14):2377-90. PubMed ID: 26822854
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Working-correlation-structure identification in generalized estimating equations.
    Hin LY; Wang YG
    Stat Med; 2009 Feb; 28(4):642-58. PubMed ID: 19065625
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.