['To assess how different imputation methods used to account for missing variance data in primary studies influence tests of heterogeneity and pooled results from a meta-analysis with continuous outcomes.', 'Point and variance estimates for changes in serum creatinine, glomerular filtration rate, systolic blood pressure, and diastolic blood pressure were variably reported among 48 primary longitudinal studies of living kidney donors (71%-78% of point estimates were reported, 8%-13% of variance data were reported). We compared the results of meta-analysis, which either were restricted to available data or used four methods to impute missing variance data. These methods used reported P-values, reported nonparametric summaries, results from other similar studies using multiple imputation, or results from estimated correlation coefficients.', 'Significant heterogeneity was present in all four outcomes regardless of the imputation methods applied. The random effects point estimates and 95% confidence intervals varied little across imputation methods, and the differences were not clinically significant.'] Do imputing variance estimates alter the conclusions of a meta-analysis with continuous outcomes : a case study of changes in renal function after living kidney donation?