Analysis of Ordinal Data

In this workshop, different types of data will be defined with examples. These include categorical, ordinal, interval, and ratio data types. There are many well-known procedures for analyzing categorical and interval/ratio data types. Because of this, many researchers treat ordinal data as categorical data in order to obtain results for an analysis. Although this approach is valid, when the ordered nature of the ordinal data is ignored, the researcher potentially sacrifices statistical power and, in specific analyses, obtains insignificant results. We plan to show procedures that are readily available in statistical packages that take into account the ordered nature of some data that can increase the power of detecting relationships between variables.

ACCREDITATION: The University at Buffalo Jacobs School of Medicine and Biomedical Sciences is accredited by the ACCME to provide continuing medical education for physicians.

CERTIFICATION: The University at Buffalo Jacobs School of Medicine and Biomedical Sciences designates this live activity for a maximum of 2.0 AMA PRA Category 1 Credit(s)TM.  Physicians should claim only the credit commensurate with the extent of their participation in the activity.

CREDIT: This program is supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under award number UL1TR001412.