Jump and Comparability Ratio Models

Trend data are often recorded or classified based on certain types of coding systems, and changes in code structure or coding rules over time are not uncommon. For example:

• ICD-9/ICD-10 cause of death coding changes,
• Coding changes in the staging of cancer.

The coding changes could cause sudden increases/decreases, or "jumps" in data, even though the underlying trends have not changed. Joinpoint models that ignore data jumps due to coding changes may produce biased estimates of trends. Two models developed to incorporate a sudden discontinuous jump in an otherwise continuous joinpoint model are:

• The Joinpoint-Comparability Ratio model (JP-CR) which utilizes a pre-estimated size of the jump from supplementary data,
• The Joinpoint-Jump model (JP-Jump) which simultaneously estimates the size of the jump, as well as the changes in trend.

The basics of these models, model selection, and examples are given in the Methods and Examples page.

Suggested Citation

Chen HS, Zeichner S, Anderson RN, Espey DK, Kim HJ, Feuer EJ. The Joinpoint-Jump and Joinpoint-Comparability Ratio Model for Trend Analysis with Applications to Coding Changes in Health Statistics. J Off Stat. 2020;36(1):49-62. doi:10.2478/jos-2020-0003.