Meta-analyses often combine covariate-adjusted effect estimates (odds ratios or relative risks) and confidence intervals relating a specified endpoint to a given exposure. Standard techniques are available to do this where the exposure is a simple presence/absence variable, or can be expressed in defined units. However, where the definition of exposure is qualitative and may vary between studies, meta-analysis is less straightforward. We have introduced a new “Uniform Scale” approach allowing expression of effect estimates in a consistent manner, comparing individuals with the most and least possible exposure. In 2008, we presented methodology and made available software in Excel and SAS to obtain estimates for specific pairwise comparisons of exposure, such as any versus none, where the source paper provided estimates for multiple exposure categories expressed relative to a common reference group. The methodology takes account of the correlation between the effect estimates for the different levels. Here we provide extended software, in Excel, SAS and R, to also obtain effect estimates per unit of exposure, whether the exposure is defined or is to be expressed in the “Uniform Scale”.