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Composite Link Functions in Generalized Linear Models
Abstract
SUMMARY In generalized linear models each observation is linked with a predicted value based on a linear function of some systematic effects. We sometimes require to link each observation with a linear function of more than one predicted value. We embed such models into the generalized linear model framework using composite link functions. The computer program GLIM-3 can be used to fit these models. Illustrative examples are given including a mixed-up contingency table and grouped normal data.
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Citations
Cited by
(2005) · Statistics for Biology and Health · doi:10.1007/0-387-27255-0_9 · Cited by 20,133
Green, P. J. (1984) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1984.tb01288.x · Cited by 687
Regression and ordered categorical variables
Anderson, J. A. (1984) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1984.tb01270.x · Cited by 574
A Mixed-Model Procedure for Analyzing Ordered Categorical Data
Harville, D. A., & Mee, R. W. (1984) · Biometrics · doi:10.2307/2531393 · Cited by 447
ORDINAL REGRESSION MODELS FOR EPIDEMIOLOGIC DATA
ARMSTRONG, B. G., & SLOAN, M. (1989) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a115109 · Cited by 320
Metadata
- Authors
- Thompson, R., & Baker, R. J.
- Venue
- Applied Statistics
- Publisher
- JSTOR
- Published
- 1981
- Volume
- 30
- Issue
- 2
- Pages
- 125
- ISSN
- 0035-9254 (ISSN-L)
- OpenAlex
- W161181078
- Cited by
- 184
- References
- 0
- FWCI
- 6.68
- Type
- journal article
- Language
- en
- Open access
- closed
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- Thompson, R., & Baker, R. J. (1981). Composite Link Functions in Generalized Linear Models. Applied Statistics. https://doi.org/10.2307/2346381
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