The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Incomplete Data in Generalized Linear Models
Abstract
This article examines incomplete data for the class of generalized linear models, in which incompleteness is due to partially missing covariates on some observations. Under the assumption that the missing data are missing at random, it is shown that the E step of the EM algorithm for any generalized linear model can be expressed as a weighted complete data log-likelihood when the unobserved covariates are assumed to come from a discrete distribution with finite range. Expressing the E step in this manner allows for a straightforward maximization in the M step, thus leading to maximum likelihood estimates (MLE's) for the parameters. Asymptotic variances of the MLE's are also derived, and results are illustrated with two examples.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
RUBIN, D. B. (1976) · Biometrika · doi:10.1093/biomet/63.3.581 · Cited by 9,925
Anderson, T. W. (1957) · Journal of the American Statistical Association · doi:10.1080/01621459.1957.10501379 · Cited by 592
Missing Values in Multivariate Analysis
Beale, E. M. L., & Little, R. J. A. (1975) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1975.tb01037.x · Cited by 343
Missing Observations in Multivariate Statistics I. Review of the Literature
Afifi, A. A., & Elashoff, R. M. (1966) · Journal of the American Statistical Association · doi:10.1080/01621459.1966.10480891 · Cited by 306
Laryngeal Complications of Prolonged Intubation
Colice, G. L., Stukel, T. A., & Dain, B. (1989) · Chest · doi:10.1378/chest.96.4.877 · Cited by 295
The Analysis of Incomplete Data
Hartley, H. O., & Hocking, R. R. (1971) · Biometrics · doi:10.2307/2528820 · Cited by 295
Maximum likelihood estimation for mixed continuous and categorical data with missing values
LITTLE, R. J. A., & SCHLUCHTER, M. D. (1985) · Biometrika · doi:10.1093/biomet/72.3.497 · Cited by 246
Moments and Distributions of Estimates of Population Parameters from Fragmentary Samples
Wilks, S. S. (1932) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177732885 · Cited by 219
Compound Poisson Regression Models
Hinde, J. (1982) · Lecture Notes in Statistics · doi:10.1007/978-1-4612-5771-4_11 · Cited by 208
Maximum Likelihood Estimation and Model Selection in Contingency Tables with Missing Data
Fuchs, C. (1982) · Journal of the American Statistical Association · doi:10.1080/01621459.1982.10477795 · Cited by 151
Cited by
Missing data: our view of the state of the art
Schafer, J. L., & Graham, J. W. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.2.147 · Cited by 11,638
Schaeffer, L., Gohlke, H., Müller, M., Heid, I. M., Palmer, L. J., Kompauer, I., Demmelmair, H., Illig, T., Koletzko, B., & Heinrich, J. (2006) · Human Molecular Genetics · doi:10.1093/hmg/ddl117 · Cited by 561
Expression of p16 INK4a in peripheral blood T‐cells is a biomarker of human aging
Liu, Y., Sanoff, H. K., Cho, H., Burd, C. E., Torrice, C., Ibrahim, J. G., Thomas, N. E., & Sharpless, N. E. (2009) · Aging Cell · doi:10.1111/j.1474-9726.2009.00489.x · Cited by 509
Self-citationHandling drop‐out in longitudinal studies
Hogan, J. W., Roy, J., & Korkontzelou, C. (2004) · Statistics in Medicine · doi:10.1002/sim.1728 · Cited by 404
Adjusting for partially missing baseline measurements in randomized trials
White, I. R., & Thompson, S. G. (2005) · Statistics in Medicine · doi:10.1002/sim.1981 · Cited by 378
Metadata
- Authors
- Ibrahim, J. G.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1990-09
- Volume
- 85
- Issue
- 411
- Pages
- 765-769
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2070337513
- Cited by
- 344
- References
- 12
- FWCI
- 3.40
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Incomplete Data in Generalized Linear Models. https://app.cochat.ai/papers/10.1080/01621459.1990.10474938
- The paper
- Ibrahim, J. G. (1990). Incomplete Data in Generalized Linear Models. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.1990.10474938
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
