Analysis of linkage data has typically been carried out assuming genotyping errors are absent. Recent studies have shown, however, that the impact of ignoring genotyping errors can be great, especially in dense marker maps [Buetow, Am J Hum Genet 1991;49:985–994; Lincoln and Lander, Genomics 1992;14:604-610]. Because most organisms exhibit positive chiasma interference, we use the χ2model [Foss et al., Genetics 1993;144:681–691] to examine the role interference plays in the estimation of genetic distance in the presence of genotyping errors. For simplicity, we confine our analyses to samples of 1,000 fully informative gametes. Our results support previous findings that ignoring errors inflates distance estimates. The larger the error rate, the greater the inflation. For a given error rate, the relative error in estimated genetic distance is greatest when interference is known to be weak or absent. An approximation to relative error which quantifies the relation to distance, error rate, and interference is provided. Robustness of estimation to error misspecification is also investigated. When the assumed error rate is too low, distance is overestimated while interference is underestimated. The situation is reversed when too large an error rate is assumed (interference is overestimated, and distance underestimated). Unfortunately, the joint estimation of distance and interference is not very robust to error misspecifica