A meta-analytic summary estimate of association often is calculated as an inverse variance weighted average of study-specific estimates of association. The variances of published estimates of association are derived from their associated confidence intervals under the assumptions typical of Wald-type statistics. However, in some research areas, epidemiological results typically are obtained by fitting linear excess relative rate models, and associated likelihood-based confidence intervals are often asymmetrical; consequently, reasonable estimates of variances associated with study-specific estimates of association may be difficult to infer from the standard approach based on the assumption of a Wald-type interval. We describe a novel method to derive estimates of variance for use in meta-analysis of published results obtained by fitting linear excess relative rate models. The approach is illustrated using a previously-published example of meta-analysis of epidemiological findings regarding circulatory disease following exposure to low-level ionizing radiation, and a new example of meta-analysis of epidemiological findings regarding leukemia following exposure to ionizing radiation from diagnostic procedures; and, the meta-analytic summary obtained using the proposed approach is compared to that obtained using the more classical approach to meta-analysis. Keywords: meta-analysis; cohort studies; excess relative risk; cancer Abbreviations: RR, relative rate; CI, confidence interval; ERR, excess relative rate; Sv, sievert.