Quantifying temporal trends of age-standardized rates with odds.

ABSTRACT:

Background

To quantify temporal trends in age-standardized rates of disease, the convention is to fit a linear regression model to log-transformed rates because the slope term provides the estimated annual percentage change. However, such log-transformation is not always appropriate.

Methods

We propose an alternative method using the rank-ordered logit (ROL) model that is indifferent to log-transformation. This method quantifies the temporal trend using odds, a quantity commonly used in epidemiology, and the log-odds corresponds to the scaled slope parameter estimate from linear regression. The ROL method can be implemented by using the commands for proportional hazards regression in any standard statistical package. We apply the ROL method to estimate temporal trends in age

SUBMITTER: Tan CS 

PROVIDER: S-EPMC6299543 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature