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Complementary Log Regression for Generalized Linear Models
Walter W. Piegorsch
The American Statistician
Vol. 46, No. 2 (May, 1992), pp. 94-99
Stable URL: http://www.jstor.org/stable/2684172
Page Count: 6
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Use and implementation of the complementary log regression model are discussed, integrating various separate applications of the model under the form of a generalized linear model. Some motivation is drawn from cases where an underlying random variable is reduced to a dichotomous form. Estimation and testing are facilitated by recognizing the complementary log as a specific link function within a generalized linear framework. Testing for goodness of link via efficient scores is also discussed.
The American Statistician © 1992 American Statistical Association