The present study assesses the effects of genotyping errors on the type I error rate of a particular transmission/disequilibrium test (TDT_std), which assumes that data are errorless, and introduces a new transmission/disequilibrium test (TDT_ae) that allows for random genotyping errors. We evaluate the type I error rate and power of the TDT_ae under a variety of simulations and perform a power comparison between the TDT_std and the TDT_ae, for errorless data. Both the TDT_std and the TDT_ae statistics are computed as two times a log-likelihood difference, and both are asymptotically distributed as χ² with 1 df. Genotype data for trios are simulated under a null hypothesis and under an alternative (power) hypothesis. For each simulation, errors are introduced randomly via a computer algorithm with different probabilities (called "allelic error rates"). The TDT_std statistic is computed on all trios that show Mendelian consistency, whereas the TDT_ae statistic is computed on all trios. The results indicate that TDT_std shows a significant increase in type I error when applied to data in which inconsistent trios are removed. This type I error increases both with an increase in sample size and with an increase in the allelic error rates. TDT_ae always maintains correct type I error rates for the simulations considered. Factors affecting the power of the TDT_ae are discussed. Finally, the power of TDT_std is at least that of TDT_ae for simulations with errorless data. Because data are rarely error free, we recommend that researchers use methods, such as the TDT_ae, that allow for errors in genotype data.