We performed error analysis of tumor blood flow (TBF) measurement using dynamic contrast-enhanced data and model-independent deconvolution analysis, based on computer simulations. For analysis, we generated a time-dependent concentration of the contrast agent in the volume of interest (VOI) from the arterial input function (AIF) consisting of gamma-variate functions using an adiabatic approximation to the tissue homogeneity model under various plasma flow (F_p), mean capillary transit time (T_c), permeability–surface area product (PS) and signal-to-noise ratio (SNR) values. Deconvolution analyses based on truncated singular value decomposition with a fixed threshold value (TSVD-F), with an adaptive threshold value (TSVD-A) and with the threshold value determined by generalized cross validation (TSVD-G) were used to estimate F_p values from the simulated concentration–time curves in the VOI and AIF. First, we investigated the relationship between the optimal threshold value and SNR in TSVD-F, and then derived the equation describing the relationship between the threshold value and SNR for TSVD-A. Second, we investigated the dependences of the estimated F_p values on T_c, PS, the total duration for data acquisition and the shape of AIF. Although TSVD-F with a threshold value of 0.025, TSVD-A with the threshold value determined by the equation derived in this study and TSVD-G could estimate the F_p values in a similar manner, the standard deviation of the estimates was the smallest and largest for TSVD-A and TSVD-G, respectively. PS did not largely affect the estimates, while T_c did in all methods. Increasing the total duration significantly improved the variations in the estimates in all methods. TSVD-G was most sensitive to the shape of AIF, especially when the total duration was short. In conclusion, this study will be useful for understanding the reliability and limitation of model-independent deconvolution analysis when applied to TBF measurement using an extravascular contrast agent.