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.
135 related articles for article (PubMed ID: 37607718)
1. A flexible quasi-likelihood model for microbiome abundance count data. Shi Y; Li H; Wang C; Chen J; Jiang H; Shih YT; Zhang H; Song Y; Feng Y; Liu L Stat Med; 2023 Nov; 42(25):4632-4643. PubMed ID: 37607718 [TBL] [Abstract][Full Text] [Related]
2. Negative binomial mixed models for analyzing microbiome count data. Zhang X; Mallick H; Tang Z; Zhang L; Cui X; Benson AK; Yi N BMC Bioinformatics; 2017 Jan; 18(1):4. PubMed ID: 28049409 [TBL] [Abstract][Full Text] [Related]
3. Randomized quantile residuals for diagnosing zero-inflated generalized linear mixed models with applications to microbiome count data. Bai W; Dong M; Li L; Feng C; Xu W BMC Bioinformatics; 2021 Nov; 22(1):564. PubMed ID: 34823466 [TBL] [Abstract][Full Text] [Related]
4. Testing latent classes in gut microbiome data using generalized Poisson regression models. Qiao X; He H; Sun L; Bai S; Ye P Stat Med; 2024 Jan; 43(1):102-124. PubMed ID: 37921025 [TBL] [Abstract][Full Text] [Related]
5. Local influence measure of zero-inflated generalized Poisson mixture regression models. Chen XD; Fu YZ; Wang XR Stat Med; 2013 Apr; 32(8):1294-312. PubMed ID: 22903860 [TBL] [Abstract][Full Text] [Related]
6. A GLM-based latent variable ordination method for microbiome samples. B Sohn M; Li H Biometrics; 2018 Jun; 74(2):448-457. PubMed ID: 28991375 [TBL] [Abstract][Full Text] [Related]
7. A GLM-based zero-inflated generalized Poisson factor model for analyzing microbiome data. Chi J; Ye J; Zhou Y Front Microbiol; 2024; 15():1394204. PubMed ID: 38873138 [TBL] [Abstract][Full Text] [Related]
8. Estimation using penalized quasilikelihood and quasi-pseudo-likelihood in Poisson mixed models. Lin X Lifetime Data Anal; 2007 Dec; 13(4):533-44. PubMed ID: 18080833 [TBL] [Abstract][Full Text] [Related]
9. Generalized partially linear single-index model for zero-inflated count data. Wang X; Zhang J; Yu L; Yin G Stat Med; 2015 Feb; 34(5):876-86. PubMed ID: 25421596 [TBL] [Abstract][Full Text] [Related]
10. A flexible count data regression model for risk analysis. Guikema SD; Coffelt JP Risk Anal; 2008 Feb; 28(1):213-23. PubMed ID: 18304118 [TBL] [Abstract][Full Text] [Related]
11. Characterizing the performance of the Conway-Maxwell Poisson generalized linear model. Francis RA; Geedipally SR; Guikema SD; Dhavala SS; Lord D; LaRocca S Risk Anal; 2012 Jan; 32(1):167-83. PubMed ID: 21801191 [TBL] [Abstract][Full Text] [Related]
12. Analyzing the overall effects of the microbiome abundance data with a Bayesian predictive value approach. Zhang X; Yi N Stat Methods Med Res; 2022 Oct; 31(10):1992-2003. PubMed ID: 35695247 [TBL] [Abstract][Full Text] [Related]
13. Consistent estimation of zero-inflated count models. Staub KE; Winkelmann R Health Econ; 2013 Jun; 22(6):673-86. PubMed ID: 22623339 [TBL] [Abstract][Full Text] [Related]
14. 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]
15. Maximum likelihood estimation for N-mixture models. Haines LM Biometrics; 2016 Dec; 72(4):1235-1245. PubMed ID: 27043770 [TBL] [Abstract][Full Text] [Related]
16. llperm: a permutation of regressor residuals test for microbiome data. Viljanen M; Boshuizen H BMC Bioinformatics; 2022 Dec; 23(1):540. PubMed ID: 36510128 [TBL] [Abstract][Full Text] [Related]
17. A simulation study of the performance of statistical models for count outcomes with excessive zeros. Zhou Z; Li D; Huh D; Xie M; Mun EY Stat Med; 2024 Oct; 43(24):4752-4767. PubMed ID: 39193779 [TBL] [Abstract][Full Text] [Related]
18. Testing latent class of subjects with structural zeros in negative binomial models with applications to gut microbiome data. Ye P; Qiao X; Tang W; Wang C; He H Stat Methods Med Res; 2022 Nov; 31(11):2237-2254. PubMed ID: 35899309 [TBL] [Abstract][Full Text] [Related]
19. NBZIMM: negative binomial and zero-inflated mixed models, with application to microbiome/metagenomics data analysis. Zhang X; Yi N BMC Bioinformatics; 2020 Oct; 21(1):488. PubMed ID: 33126862 [TBL] [Abstract][Full Text] [Related]
20. On the EM algorithm for overdispersed count data. McLachlan GJ Stat Methods Med Res; 1997 Mar; 6(1):76-98. PubMed ID: 9185291 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]