PubMed · 9085093
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M I Wallhagen. 1997. Logistic regression formula corrected.. https://pubmed.ncbi.nlm.nih.gov/9085093/
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Double saddlepoint approximations provide quick and accurate approximations to exact conditional tail probabilities in a variety of situations. This paper describes the use of these approximations in two logistic regression problems. An investigation of regression analysis of the log-odds ratio in a sequence or set of 2x2 tables via simulation studies shows that in practical settings the saddlepoint methods closely approximate exact conditional inference. The double saddlepoint approximation in the test for trend in a sequence of binomial random variates is also shown, via simulation studies, to be an effective approximation to exact conditional inference.
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It is highly to observe in the biomedical literature, that the continuous variables such as systolic blood pressure and cholesterol, are dichotomized and used in such manner in a given statistical analysis. The consequences of such transformation can be very varied. In this article, how the dichotomization of a continuous exposure variable affects the quality of the prediction of a response using the logistic regression is examined. One can conclude that, in almost all the studied stimulation, the percentages of misclassification can increase drastically, reaching over there times the probability of misclassification of the ones using the original variable. Therefore, we recommend to avoid dichotomization.