1 / 20

An Illustration of Rate Difference Estimation with SAS in Logistic Regression

An Illustration of Rate Difference Estimation with SAS in Logistic Regression. Yun Guo. Outline. Statistical methods for RD RD with logistic regression SAS realization Conclusion. Statistical methods. Wald/t approximation—no covariate adjust CMH (weighted estimate)-adjust strata

kanoa
Download Presentation

An Illustration of Rate Difference Estimation with SAS in Logistic Regression

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. An Illustration of Rate Difference Estimation with SAS in Logistic Regression Yun Guo

  2. Outline • Statistical methods for RD • RD with logistic regression • SAS realization • Conclusion

  3. Statistical methods • Wald/t approximation—no covariate adjust • CMH (weighted estimate)-adjust strata • Logistic Regression-adjust both

  4. Statistical methods • Logistic regression ,where, x is covariate, s is factor, t is treatment, sub i is indexing subject (1) (2)

  5. RD with logistic regression • Odd Ratio through Logistic Regression Simply subtract among different levels of factor Say t(t=1) vs. t(t=0),

  6. RD with logistic regression • Rate through Logistic Regression (say subject i=1) (3) Intercept, covariate as well as factor, not gone!!!!

  7. RD with logistic regression • How about the variance of estimate? (4) Very messy!!!

  8. RD with logistic regression Hereafter subscript 1/0 of est p index treatment.

  9. Statistical methods • Marginal approach (sum over all samples)

  10. Statistical methods

  11. Statistical methods • To conclude, we have following 4 steps • 1, establish logistic regression • 2, get estimated rates, covariance of estimates, estimated RD • 3, set up Delta method • 4, get CI

  12. SAS realization EXAMPLE DATA

  13. SAS realization PREPARE DATA

  14. SAS realization STEP 1: Logistic regression

  15. SAS realization STEP 1: Logistic regression

  16. SAS realization STEP 1: Logistic regression COV EST

  17. SAS realization STEP 2: RD estimate

  18. SAS realization Step 3: Delta method Step 4: CI

  19. Conclusion 1, When covariates adjust needed, a choice is to use L Regression 2, Other methods could be used too

  20. Thank you!

More Related