# Can the confidence interval of an odds ratio be negative? [duplicate]

I am running logistic regression.

The odds ratio estimate I got is positive but the lower bound of my 95% CI is negative (close to -1) and the upper bound is greater than 1. Would this mean that my result is not statistically significant?

In a hypothetical case that the odds ratio 95% CI is something like (-1, .5), would this also mean it is not statistically significant? The odds ratio in this hypothetical situation is not 0 or negative.

I used stargazer in R to get the 95% CIs, and these are the optional arguments I put in stargazer: apply.coef = exp,ci = TRUE, ci.level = .95

• 1. The "baseline" for an insignificant odds ratio is 1 - when there's no difference in the probability of the two events - so yes, this means your result is not significant at the 95% level of confidence. 2. The odds ratio cannot be negative, but, if the CI is calculated using approximations to the true distribution, the calculated CI can contain negative numbers. Commented May 21, 2023 at 1:57
• @jbowman one more question, first thanks for your response! according to the stargazer documentation the p-values calculated are with normal distribution since I specified apply.coef = exp. My question is, regarding a negative value in the lower bound of the CIs, would the same interpretation hold true for binomial or poisson distributions? Commented May 21, 2023 at 2:14
• Yes, doubly so with the binomial probability parameter as it's bounded both above and below. Commented May 21, 2023 at 2:22
• @jbowman thank you so much! Commented May 21, 2023 at 2:25

• two more questions, first thanks for pointing that out. 1. regardless of the distribution type, negative 95% CIs for odds ratios cannot exist? 2. I checked with the MASS library in R (r-bloggers.com/2011/11/…) using its confint.default and got realistic 95% CIs, not sure if you use R but do you know why stargazer (cran.r-project.org/web/packages/stargazer/stargazer.pdf) would give those answers? Commented May 21, 2023 at 4:41