Multiple Imputation of Missing Data had Little Effect on Breast Cancer Results. Adjusted, 20 years of Latency. a) Breast cancer map estimated using indicator variables to signify missing covariate data (Fig. 3c). b) We imputed missing data for covariates missing 10% or more of values. We generated six data sets, applying the GAM model to each. All maps (and their average) looked virtually identical; only one is shown, drawn using the same span (0.15) as the non-imputed map in a. c) Imputed map drawn using its optimal span of 0.35. Since the span is larger, it appears smoother than in b. The global statistics for all imputed maps were highly significant, regardless of span size. Black contour lines denote areas of significantly increased and decreased risk at the 0.05 level.