224 related articles for article (PubMed ID: 34991359)
1. Marginal modeling in community randomized trials with rare events: Utilization of the negative binomial regression model.
Westgate PM; Cheng DM; Feaster DJ; Fernández S; Shoben AB; Vandergrift N
Clin Trials; 2022 Apr; 19(2):162-171. PubMed ID: 34991359
[TBL] [Abstract][Full Text] [Related]
2. A readily available improvement over method of moments for intra-cluster correlation estimation in the context of cluster randomized trials and fitting a GEE-type marginal model for binary outcomes.
Westgate PM
Clin Trials; 2019 Feb; 16(1):41-51. PubMed ID: 30295512
[TBL] [Abstract][Full Text] [Related]
3. Intra-cluster correlation selection for cluster randomized trials.
Westgate PM
Stat Med; 2016 Aug; 35(19):3272-84. PubMed ID: 26924419
[TBL] [Abstract][Full Text] [Related]
4. Sample size estimation for modified Poisson analysis of cluster randomized trials with a binary outcome.
Li F; Tong G
Stat Methods Med Res; 2021 May; 30(5):1288-1305. PubMed ID: 33826454
[TBL] [Abstract][Full Text] [Related]
5. Power and sample size calculations for cluster randomized trials with binary outcomes when intracluster correlation coefficients vary by treatment arm.
Kennedy-Shaffer L; Hughes MD
Clin Trials; 2022 Feb; 19(1):42-51. PubMed ID: 34879711
[TBL] [Abstract][Full Text] [Related]
6. Performance of analytical methods for overdispersed counts in cluster randomized trials: sample size, degree of clustering and imbalance.
Durán Pacheco G; Hattendorf J; Colford JM; Mäusezahl D; Smith T
Stat Med; 2009 Oct; 28(24):2989-3011. PubMed ID: 19672840
[TBL] [Abstract][Full Text] [Related]
7. Analysis of hypoglycemic events using negative binomial models.
Luo J; Qu Y
Pharm Stat; 2013; 12(4):233-42. PubMed ID: 23776062
[TBL] [Abstract][Full Text] [Related]
8. Comparative assessment of parameter estimation methods in the presence of overdispersion: a simulation study.
Roosa K; Luo R; Chowell G
Math Biosci Eng; 2019 May; 16(5):4299-4313. PubMed ID: 31499663
[TBL] [Abstract][Full Text] [Related]
9. GEEMAEE: A SAS macro for the analysis of correlated outcomes based on GEE and finite-sample adjustments with application to cluster randomized trials.
Zhang Y; Preisser JS; Li F; Turner EL; Toles M; Rathouz PJ
Comput Methods Programs Biomed; 2023 Mar; 230():107362. PubMed ID: 36709555
[TBL] [Abstract][Full Text] [Related]
10. Performance of model-based vs. permutation tests in the HEALing (Helping to End Addiction Long-term
Tang X; Heeren T; Westgate PM; Feaster DJ; Fernandez SA; Vandergrift N; Cheng DM
Trials; 2022 Sep; 23(1):762. PubMed ID: 36076295
[TBL] [Abstract][Full Text] [Related]
11. Overdispersion models for correlated multinomial data: Applications to blinding assessment.
Landsman V; Landsman D; Li CS; Bang H
Stat Med; 2019 Nov; 38(25):4963-4976. PubMed ID: 31460677
[TBL] [Abstract][Full Text] [Related]
12. On performance of parametric and distribution-free models for zero-inflated and over-dispersed count responses.
Tang W; Lu N; Chen T; Wang W; Gunzler DD; Han Y; Tu XM
Stat Med; 2015 Oct; 34(24):3235-45. PubMed ID: 26078035
[TBL] [Abstract][Full Text] [Related]
13. Adjusting for overdispersion in piecewise exponential regression models to estimate excess mortality rate in population-based research.
Luque-Fernandez MA; Belot A; Quaresma M; Maringe C; Coleman MP; Rachet B
BMC Med Res Methodol; 2016 Oct; 16(1):129. PubMed ID: 27716079
[TBL] [Abstract][Full Text] [Related]
14. A comparison of observation-level random effect and Beta-Binomial models for modelling overdispersion in Binomial data in ecology & evolution.
Harrison XA
PeerJ; 2015; 3():e1114. PubMed ID: 26244118
[TBL] [Abstract][Full Text] [Related]
15. Evaluation of negative binomial and zero-inflated negative binomial models for the analysis of zero-inflated count data: application to the telemedicine for children with medical complexity trial.
Lee KH; Pedroza C; Avritscher EBC; Mosquera RA; Tyson JE
Trials; 2023 Sep; 24(1):613. PubMed ID: 37752579
[TBL] [Abstract][Full Text] [Related]
16. Multiply robust generalized estimating equations for cluster randomized trials with missing outcomes.
Rabideau DJ; Li F; Wang R
Stat Med; 2024 Mar; 43(7):1458-1474. PubMed ID: 38488532
[TBL] [Abstract][Full Text] [Related]
17. Application of negative binomial modeling for discrete outcomes: a case study in aging research.
Byers AL; Allore H; Gill TM; Peduzzi PN
J Clin Epidemiol; 2003 Jun; 56(6):559-64. PubMed ID: 12873651
[TBL] [Abstract][Full Text] [Related]
18. A comparison of generalized linear mixed model procedures with estimating equations for variance and covariance parameter estimation in longitudinal studies and group randomized trials.
Evans BA; Feng Z; Peterson AV
Stat Med; 2001 Nov; 20(22):3353-73. PubMed ID: 11746323
[TBL] [Abstract][Full Text] [Related]
19. Robust inference in the negative binomial regression model with an application to falls data.
Aeberhard WH; Cantoni E; Heritier S
Biometrics; 2014 Dec; 70(4):920-31. PubMed ID: 25156188
[TBL] [Abstract][Full Text] [Related]
20. Comparison of population-averaged and cluster-specific models for the analysis of cluster randomized trials with missing binary outcomes: a simulation study.
Ma J; Raina P; Beyene J; Thabane L
BMC Med Res Methodol; 2013 Jan; 13():9. PubMed ID: 23343209
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]