Judging Inference Adequacy in Logistic Regression. Jennings, D. E. JASA, 81(394):471-476, Taylor & Francis, 1986. doi abstract bibtex Abstract Inference for logistic regression based on the information matrix may be poor. This is noted in two examples in which confidence regions are examined. A measure to detect such inadequacies is presented; it judges the quadratic approximation to the likelihood surface, which justifies the usual procedure.
@article{jen86jud,
title = {Judging {{Inference Adequacy}} in {{Logistic Regression}}},
volume = {81},
abstract = {Abstract Inference for logistic regression based on the information matrix may be poor. This is noted in two examples in which confidence regions are examined. A measure to detect such inadequacies is presented; it judges the quadratic approximation to the likelihood surface, which justifies the usual procedure.},
number = {394},
journal = {JASA},
doi = {10.1080/01621459.1986.10478292},
author = {Jennings, Dennis E.},
year = {1986},
keywords = {maximum-likelihood,confidence-intervals,logistic-model,binary-logistic-model},
pages = {471-476},
eprint = {http://amstat.tandfonline.com/doi/pdf/10.1080/01621459.1986.10478292},
publisher = {Taylor & Francis},
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