The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Consistent Estimators in Generalized Linear Mixed Models
Abstract
A simple method based on simulated moments is proposed for estimating the fixed-effects and variance components in a generalized linear mixed model (GLMM). It is shown that the method is not only computationally attractive but also leads to consistent estimators. On the other hand, simulation shows that the method can be quite inefficient.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“In imbalanced situations, “pseudo-bulk” methods also cause cells from individuals with fewer cells to be more heavily weighted, where mixed models have consistent estimators and do not require balanced data29.”
From A practical solution to pseudoreplication bias in single-cell studies (2021) · cites this paper as [29]
Citations
Cites
(2005) · Springer eBooks · doi:10.1007/0-387-27255-0_9 · Cited by 20,333
McCullagh, P., & Nelder, J. A. (1989) · doi:10.1007/978-1-4899-3242-6 · Cited by 16,836
Approximate Inference in Generalized Linear Mixed Models
Breslow, N. E., & Clayton, D. G. (1993) · Journal of the American Statistical Association · doi:10.1080/01621459.1993.10594284 · Cited by 4,662
Searle, S. R., Casella, G., & McCulloch, C. E. (1992) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316856 · Cited by 1,926
Approximate Inference in Generalized Linear Mixed Models
(1993) · doi:10.2307/2290687 · Cited by 1,800
McFadden, D. L. (1989) · Econometrica · doi:10.2307/1913621 · Cited by 1,627
Generalized linear models. 2nd ed.
McCullagh, P., & Nelder, J. (1993) · Journal of the American Statistical Association · doi:10.2307/2290358 · Cited by 1,581
Journal of the Royal Statistical Society.
(1921) · The Economic Journal · doi:10.1093/ej/31.121.133 · Cited by 1,503
Estimation in Generalized Linear Models with Random Effects
Schall, R. (1991) · Biometrika · doi:10.1093/biomet/78.4.719 · Cited by 1,230
Hierarchical Generalized Linear Models
Lee, Y., & Nelder, J. A. (1996) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1996.tb02105.x · Cited by 958
Research works printed but not linked: 2
- Clayton D. G., 1996, Journal of the Royal Statistical Society, 58, 657
- Jiang J., 1996, “Inconsistent and Consistent Estimates in Generalized Linear Mixed Models,”
Cited by
Sorted by citations
Items 101–147 of 147
Longitudinal Mixed Models for Count Data
Sutradhar, B. C. (2011) · Springer series in statistics · doi:10.1007/978-1-4419-8342-8_8 · Cited by 1
Robust quasi-likelihood inference in generalized linear mixed models with outliers
Sutradhar, B. C., & Bari, W. (2010) · Journal of Statistical Computation and Simulation · doi:10.1080/00949650903268023 · Cited by 1
Area-Level Poisson Mixed Models
Morales, D., Esteban, M. D., Pérez, A., & Hobza, T. (2020) · Statistics for social and behavioral sciences · doi:10.1007/978-3-030-63757-6_20 · Cited by 1
EBPs Under Unit-Level Logit Mixed Models
Morales, D., Esteban, M. D., Pérez, A., & Hobza, T. (2020) · Statistics for social and behavioral sciences · doi:10.1007/978-3-030-63757-6_14 · Cited by 1
Jiang, J. (2021) · Springer texts in statistics · doi:10.1007/978-3-030-91695-4_15 · Cited by 1
Self-citationGoodness of fit tests for generalized linea mixed models
Tang, M. (2010) · University Libraries (University of Maryland) · Cited by 1
Methods and Applications in the Analysis of Correlated Non-Gaussian Data
Withanage, N. (2013) · Libraries and Cultural Resources (University of Calgary) · doi:10.11575/prism/26894 · Cited by 1
Comparação de métodos de estimação em pequenas áreas para proporções: o caso da TIC Educação
Coelho, I. B. (2016) · doi:10.11606/d.45.2016.tde-24052016-140530 · Cited by 1
Longitudinal Mixed Models for Binary Data
Sutradhar, B. C. (2011) · Springer series in statistics · doi:10.1007/978-1-4419-8342-8_9 · Cited by 1
Jiang, J. (2021) · Springer texts in statistics · doi:10.1007/978-3-030-91695-4_4 · Cited by 1
Self-citationChen, P., Yang, X., Winters, P. L., Li, M., Rodrı́guez, D. A., Montilla, M., & Chatman, D. G. (2021) · doi:10.5038/cutr-nicr-y1-3.3 · Cited by 1
Familial Longitudinal Models for Binary Data
Sutradhar, B. C. (2011) · Springer series in statistics · doi:10.1007/978-1-4419-8342-8_11 · Cited by 1
Sun, B. (2014) · Memorial University Research Repository (Memorial University) · Cited by 1
On Implementation of the Markov Chain Monte Carlo Stochastic Approximation Algorithm
Jiang, Y., Karcher, P., & Wang, Y. (2010) · Physica-Verlag eBooks · doi:10.1007/978-3-7908-2628-9_7 · Cited by 1
Familial Models for Count Data
Sutradhar, B. C. (2011) · Springer series in statistics · doi:10.1007/978-1-4419-8342-8_4
Estimation for Single-Index mixed models with Longitudinal dataPreprint
Pang, Z., & Xue, L. (2010) · arXiv (Cornell University) · doi:10.48550/arxiv.1004.0482
Topics On Generalized Linear Mixed Models
Zipunnikov, V. (2009) · eCommons (Cornell University)
Multivariate approach for protein identification based on mass spectrometric data
Lee, J. B., & Lee, J. W. (2012) · Statistical Methods in Medical Research · doi:10.1177/0962280211434960
Complex sampling design based inference on familial models for count data
Granter, L. I. (2007) · Memorial University Research Repository (Memorial University)
ATINER's Conference Paper Series STA2014-1255
Jowaheer, V., & Sutradhar, B. C. (2014)
A New Framework for Random Effects ModelsPreprint
Matloff, N. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1511.03761
Robust estimation in familial and longitudinal models
Bari, W. (2007) · Memorial University Research Repository (Memorial University)
A classical approach for the analysis of generalized linear mixed models.
Hammujuddy, M. J. (2004) · ResearchSpace (University of KwaZulu-Natal)
Longitudinal Mixed Models with t Random Effects for Repeated Count and Binary Data
Rao, R. P., Sutradhar, B. C., & Pandit, V. (2016) · Lecture notes in statistics · doi:10.1007/978-3-319-31260-6_2
Variance Components Testing in Nonlinear Random Effects Models
Nono, J. P. (2002)
Generalized Linear Mixed-Effects Models for the Analysis of Odor Detection Data
Hall, S., Mayo, M. S., Niu, X., & Walker, J. C. (2007) · Journal of Modern Applied Statistical Methods · doi:10.22237/jmasm/1193891040
Lu, Y., Chen, Z., & Durán, D. (2017) · Communications in Statistics - Simulation and Computation · doi:10.1080/03610918.2017.1361979
Mariathas, H. H., Asghari, S., Hurley, O., Anaraki, N. R., Young, C., Aubrey‐Bassler, K., Wang, P., Gadag, V. G., Nguyen, H. V., Etchegary, H., et al. (2021) · doi:10.2196/preprints.30454
Rao, J. N. K., & Molina, I. (2015) · Wiley eBooks · doi:10.1002/9781118735855.refs
Jiang, J. (2021) · Springer texts in statistics · doi:10.1007/978-3-030-91695-4_5
Self-citation(2003) · Wiley eBooks · doi:10.1002/0471722189.refs
Editors, J. (2007) · Journal of Modern Applied Statistical Methods · doi:10.22237/jmasm/1193891520
Familial Models for Binary Data
Sutradhar, B. C. (2011) · Springer series in statistics · doi:10.1007/978-1-4419-8342-8_5
(2009) · Handbook of statistics · doi:10.1016/s0169-7161(09)70062-8
Generalized Linear Mixed Models: Part I
Jiang, J., & Nguyen, T. D. (2021) · Springer series in statistics · doi:10.1007/978-1-0716-1282-8_3
Self-citationSutradhar, B. C. (2011) · Springer series in statistics · doi:10.1007/978-1-4419-8342-8_1
On Estimation of the Logarithm of the Mean Squared Prediction Error of A Mixed-effect Predictor
Wang, J., Nguyen, T. D., Luan, Y., & Jiang, J. (2022) · Statistica Sinica · doi:10.5705/ss.202022.0043
Self-citationCovariance based moment equations for improved variance component estimation
Chaudhuri, S., Kubokawa, T., & Sugasawa, S. (2022) · Statistics · doi:10.1080/02331888.2022.2144856
Song, Y., & Wang, R. (2023) · Statistical Methods in Medical Research · doi:10.1177/09622802231181225
A Generalization of the Spatial Binary Model to the Longitudinal Spatial Setup
Sutradhar, B. C. (2023) · Sankhya A · doi:10.1007/s13171-023-00319-5
Novellis, G. D., Doretti, M., Montanari, G. E., Ranalli, M. G., & Salvati, N. (2024) · Statistical Methods & Applications · doi:10.1007/s10260-024-00757-x
Fitting a binomial mixed logistic model with improved accuracy and computational efficiency
Tan, X., & Jiang, J. (2026) · Journal of Statistical Computation and Simulation · doi:10.1080/00949655.2026.2701362
Self-citationNeale (2000) · doi:10.1002/(sici)1098-2272(200004)18:4
Metadata
- Authors
- Jiang, J.
- Affiliations
- Case Western Reserve University (US)
- Corresponding author
- Jiang, Jiming
- ORCID
- Jiang, Jiming
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1998-06
- Volume
- 93
- Issue
- 442
- Pages
- 720-729
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2132137727
- Cited by
- 149
- References
- 24
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 3 · 2023: 3 · 2022: 5 · 2021: 13 · 2020: 3 · 2019: 2 · 2018: 3 · 2017: 4 · 2016: 4 · 2015: 5 · 2014: 4 · 2013: 4 · 2012: 5
- FWCI
- 5.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of the American Statistical Association (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Markov Chains and Monte Carlo Methods
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Distribution Estimation and Applications
- Keywords
- generalized linear mixed models, consistent estimators, fixed effects estimation, variance component estimation, computational efficiency
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review