1
$\begingroup$

I am at the univariable stage of my analysis, and I am looking at significance of individual variables/predictors. I've tested each predictor for significance by Wilcoxon Rank-Sum for continuous variables (not using t-test because data are not necessarily normal) and chi-square for discrete variables. However, in addition to p-values, I also need to calculate odds ratios (and 95%CI for the OR) for each predictor.

I was able to calculate ORs for the discrete variables using the (ad)/(cb) shortcut with a simple 2x2 table. But I cannot find instructions for how to calculate univariable ORs for the continuous variables.

Should I run a separate logistic regression for each of the variables, where the independent variable is the continuous predictor and the dependent variable is my 0/1 outcome?

Any help is appreciated!

$\endgroup$
5
  • $\begingroup$ This sounds like some kind of variable selection for a regression model. Is that what you're doing? $\endgroup$
    – Dave
    Commented Jun 7, 2021 at 20:53
  • 2
    $\begingroup$ What is a "univariable stage of my analysis" ? Please do NOT use the "significance" of variables in univariable regression models to inform which variables to use in a multivariable regression model. This is a terrible mistake. $\endgroup$ Commented Jun 7, 2021 at 20:56
  • $\begingroup$ @RobertLong Yes, understood. No, I'm not hunting for p-values. Working on a manuscript and need to report significance of predictors in both univariable and multivariable analysis. $\endgroup$ Commented Jun 7, 2021 at 21:01
  • $\begingroup$ Why in the univariate case? You don't have to do every statistically dubious suggestion a reviewer makes. $\endgroup$
    – Dave
    Commented Jun 7, 2021 at 21:02
  • $\begingroup$ I'm glad you understand :) but in what sense is the significance of variables in univariate models relevant to your research question(s) ? How will these be used ? $\endgroup$ Commented Jun 7, 2021 at 21:03

1 Answer 1

2
$\begingroup$

There is no straightforward way to compute odds ratios manually for continuous predictors. You need to run a one-predictor logistic regression, exponentiate the coefficient on the predictor and its confidence bounds, and then report that as the odds ratio and its 95% confidence interval. You can (and maybe should) do this with your binary predictors as well.

$\endgroup$
1
  • $\begingroup$ I realized this was a possibility just after posting. Thanks, Noah. I'm so used to working with multivariable regressions that I forgot univariable regressions are a thing, too :-) $\endgroup$ Commented Jun 7, 2021 at 20:56

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.