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 *

159 related articles for article (PubMed ID: 28426896)

  • 1. A note on marginalization of regression parameters from mixed models of binary outcomes.
    Hedeker D; du Toit SHC; Demirtas H; Gibbons RD
    Biometrics; 2018 Mar; 74(1):354-361. PubMed ID: 28426896
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Comparison of population-averaged and subject-specific approaches for analyzing repeated binary outcomes.
    Hu FB; Goldberg J; Hedeker D; Flay BR; Pentz MA
    Am J Epidemiol; 1998 Apr; 147(7):694-703. PubMed ID: 9554609
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Marginalized binary mixed-effects models with covariate-dependent random effects and likelihood inference.
    Wang Z; Louis TA
    Biometrics; 2004 Dec; 60(4):884-91. PubMed ID: 15606408
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Interpretation of mixed models and marginal models with cohort attrition due to death and drop-out.
    Rouanet A; Helmer C; Dartigues JF; Jacqmin-Gadda H
    Stat Methods Med Res; 2019 Feb; 28(2):343-356. PubMed ID: 28784010
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Models for longitudinal data: a generalized estimating equation approach.
    Zeger SL; Liang KY; Albert PS
    Biometrics; 1988 Dec; 44(4):1049-60. PubMed ID: 3233245
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Random effects probit and logistic regression models for three-level data.
    Gibbons RD; Hedeker D
    Biometrics; 1997 Dec; 53(4):1527-37. PubMed ID: 9423267
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Multivariate longitudinal data analysis with mixed effects hidden Markov models.
    Raffa JD; Dubin JA
    Biometrics; 2015 Sep; 71(3):821-31. PubMed ID: 25761965
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A need for speed in Bayesian population models: a practical guide to marginalizing and recovering discrete latent states.
    Yackulic CB; Dodrill M; Dzul M; Sanderlin JS; Reid JA
    Ecol Appl; 2020 Jul; 30(5):e02112. PubMed ID: 32112492
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Marginalized multilevel hurdle and zero-inflated models for overdispersed and correlated count data with excess zeros.
    Kassahun W; Neyens T; Molenberghs G; Faes C; Verbeke G
    Stat Med; 2014 Nov; 33(25):4402-19. PubMed ID: 24957791
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Marginalized random effects models for multivariate longitudinal binary data.
    Lee K; Joo Y; Yoo JK; Lee J
    Stat Med; 2009 Apr; 28(8):1284-300. PubMed ID: 19156673
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A random-effects ordinal regression model for multilevel analysis.
    Hedeker D; Gibbons RD
    Biometrics; 1994 Dec; 50(4):933-44. PubMed ID: 7787006
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Prediction of an outcome using trajectories estimated from a linear mixed model.
    Maruyama N; Takahashi F; Takeuchi M
    J Biopharm Stat; 2009 Sep; 19(5):779-90. PubMed ID: 20183443
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A population-averaged approach to diagnostic test meta-analysis.
    Preisser JS; Inan G; Powers JM; Chu H
    Biom J; 2019 Jan; 61(1):126-137. PubMed ID: 30370548
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Multilevel logistic regression modelling with correlated random effects: application to the Smoking Cessation for Youth study.
    Wang K; Lee AH; Hamilton G; Yau KK
    Stat Med; 2006 Nov; 25(22):3864-76. PubMed ID: 16345119
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Multiple imputation of missing covariate values in multilevel models with random slopes: a cautionary note.
    Grund S; Lüdtke O; Robitzsch A
    Behav Res Methods; 2016 Jun; 48(2):640-9. PubMed ID: 25939979
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A simulation study to assess statistical methods for binary repeated measures data.
    Masaoud E; Stryhn H
    Prev Vet Med; 2010 Feb; 93(2-3):81-97. PubMed ID: 20004989
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Estimation of average treatment effect with incompletely observed longitudinal data: application to a smoking cessation study.
    Chen HY; Gao S
    Stat Med; 2009 Aug; 28(19):2451-72. PubMed ID: 19462416
    [TBL] [Abstract][Full Text] [Related]  

  • 18. The special case of the 2 × 2 table: asymptotic unconditional McNemar test can be used to estimate sample size even for analysis based on GEE.
    Borkhoff CM; Johnston PR; Stephens D; Atenafu E
    J Clin Epidemiol; 2015 Jul; 68(7):733-9. PubMed ID: 25510372
    [TBL] [Abstract][Full Text] [Related]  

  • 19. What can go wrong when ignoring correlation bounds in the use of generalized estimating equations.
    Sabo RT; Chaganty NR
    Stat Med; 2010 Oct; 29(24):2501-7. PubMed ID: 20690109
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 8.