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Comment
. 2021 Feb 1;132(2):365-366.
doi: 10.1213/ANE.0000000000005247.

Logistic Regression in Medical Research

Patrick Schober  1 , Thomas R Vetter  2
Affiliations
Comment

Logistic Regression in Medical Research

Patrick Schober et al. Anesth Analg. .
No abstract available

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Figures

Figure.
Figure.
Relationship between a continuous independent variable X and a binary outcome that can take values 0 (eg, “no”) or 1 (eg, “yes”). As shown, the probability that the value of the outcome is 1 seems to increase with increasing values of X. A, Using a straight line to model the relationship of the independent variable with the probability provides a poor fit; results in estimated probabilities <0 and >1; and grossly violates the assumptions of linear regression. Logistic regression models a linear relationship of the independent variable with the natural logarithm (ln) of the odds of the outcome variable. B, This translates to a sigmoid relationship between the independent variable and the probability of the outcome being 1, with predicted probabilities appropriately constrained between 0 and 1.
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Comment on

References

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