Ordinal Logistic Regression Analyses
Besides the binomial logistic regression analyses discussed in the module, UniLogistic macro can be employed for conducting ordinal (proportional-odds) logistic regression analyses when the outcome has an inherent order. The mechanics of conducting analyses are exactly similar to that of the binomial logistic regression except the modeltype statement:
modeltype = ordinal, /* Type of outcome variable */
The rest of the procedure remains the same as the binomial logistic regression discussed in the module.
Example
We will use the dataset LOWBWT (Low Birth Weight) for conducting ordinal logistic regression analyses using the UniLogistic macro. This dataset is from a study conducted to investigate factors associated with low birth weight and is described in detail in Applied Logistic Regression by Hosmer and Lemeshow (2000) (© John Wiley & Sons Inc).
You can download this dataset and the implementation code used to analyse this data. We have also included the UniLogistic macro, though you do not need to download it again if you downloaded it already.
- Dataset.
- Dataset description (from the University of Massachusetts website): http://www.umass.edu/statdata/statdata/data/lowbwt.txt
- Implementation code (sas)
- Unilogistic macro (sas)
- We have included here a video demonstrating use of the macro for conducting ordinal logistic regression analyses and the output files produced by the macro.Download Demonstration Video (wmv) (40.6MB; 2.40min)
- Output file (xls)
- Graphics files (Histograms (pdf), Box-plots (pdf), Bar charts (pdf) , Stacked bar charts (pdf) ).
Note - the results are presented in a similar format to the binomial logistic regression. Of course, interpretation of some estimates, particularly odds ratios, will be different for ordinal analyses from binomial logistic regression. Please consult a statistician or read the additional resources listed on this website, if unsure.