Abstract
Analysis of causes of death is crucial for monitoring an epidemiological situation and for developing adequate policy responses. However, the comparability of cause-specific mortality data depends on the proportion of ill-defined deaths. To eliminate the bias resulting from the varying proportions of such causes over time and between populations, deaths from ill-defined causes need to be reassigned to other categories. We provide thorough documentation of and tools for the practical implementation of a regression-based method for redistributing ill-defined causes of death, as first proposed by Sully Ledermann in the 1950s. The method relies on subnational cause-specific mortality data to estimate unbiased death rates at both national and subnational levels. We refine Ledermann's method by elaborating on its mathematical properties, making additional adjustments, and evaluating the performance of the approach through simulations. To illustrate the practical application of the method, we rely on French subnational cause-of-death data and provide the R code for performing all calculations.