Hand Calculation of Odds Ratio Using JMP Results
Calculate Odds Ratio by hand
using JMP results
Meichen Dong
12/16/2021
Example: sal1.jmp
Y: ybin
Fixed Effects: fpop, mpop, fpop*mpop
Random Effects: fpop*fnum, mpop*mnum
Right click on ‘Parameter Estimates’ table in the JMP report
Select “Make into data table”, and you will
derive a new table as below:
Using the parameter estimate table
Odds Ratio calculation example:
•
https://www.proteus.co.nz/news-tips-and-tricks/how-to-calculate-
odds-ratios-from-logistic-regression-coefficients/
•
This link provides a simple example of how to calculate OR by hand. I
hope this can help!
If you want more customized results:
Please try to click on the red triangle at
the top, and select Estimates > Custom
Test.
95% CI
Learn how to manually calculate odds ratios using JMP results. Follow step-by-step instructions to convert parameter estimates, derive odds ratios, and interpret results with confidence. Enhance your statistical analysis skills today!
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Presentation Transcript
Calculate Odds Ratio by hand using JMP results Meichen Dong 12/16/2021
Example: sal1.jmp Y: ybin Fixed Effects: fpop, mpop, fpop*mpop Random Effects: fpop*fnum, mpop*mnum
Right click on Parameter Estimates table in the JMP report Select Make into data table , and you will derive a new table as below:
Using the parameter estimate table Select estimate and std err columns Right click Select New Formula Column > Transform since we used logit link for binomial outcome, which is the form of log ? = ? + ?? + ??. 1 ? The odds ratio can be derived by taking the exponential of the estimates. You will get two new columns:
Odds Ratio calculation example: https://www.proteus.co.nz/news-tips-and-tricks/how-to-calculate- odds-ratios-from-logistic-regression-coefficients/ This link provides a simple example of how to calculate OR by hand. I hope this can help!
If you want more customized results: Please try to click on the red triangle at the top, and select Estimates > Custom Test.
95% CI For example, our estimate for the parameter fpop s coefficient is 0.68, with stderr = 0.38. This means, controlling for other variables, ??????= exp 0.68 1.97 95% CI by hand: Lower limit: 0.68 1.96 0.38 = 0.0648,?? = exp 0.0648 0.94 Upper limit: 0.68 + 1.96 0.38 = 1.4248, ?? = exp 1.4248 4.16 In sum, the 95% CI is (0.94, 4.16), which includes 1, indicating that the OR for this variable is not statistically significant. Hence, you need to create two new columns: SEE THE FOLLOWING PAGE If your variable of interest is continuous, then that means for 1 unit increment, the likelihood increase by xxx. Nominal, then that means the OR between the selected level to the reference level.
