Bayesian bias adjustments of the lung cancer SMR in a cohort of German carbon black production workers

Table 1 Gaussian prior distributions (mean μ and standard deviation σ) applied in the four analyses.

One effect specification was used throughout to describe the prior for smoking (log OR_smoke). Two effect specifications were applied to estimate the effect of previous exposures (log OR_prev): one was based on CAREX data (Analyses 1 and 2) and a second based on data assessed by a German expert (Analyses 3 and 4). The proportion of male smokers in the population was estimated in all analyses by a representative sample from the male population (logit prop_{smoke, pop}). Two estimates were derived for the cohort percentage (logit prop_{smoke, coh}): one based on cohort data (Analyses 1 and 3) and a second based on case-control information (Analyses 2 and 4). The prevalence of previous occupational exposure to crystalline silica (logit prop_{prev, pop}) was estimated by the CAREX system (Analyses 1 and 2) or adapted to fit to the German's expert data (Analyses 3 and 4). The proportion of silica exposed males in the cohort (logit prop_{prev, coh}) was derived from CAREX data (Analyses 1 and 2) or from assessments of the German expert (Analyses 3 and 4). For the SMR we always used a flat prior: log SMR ~ N(0,10⁸).

ISSN: 1745-6673