AbstractGeneral or case II interval‐censored data are commonly encountered in practice. We develop methods for model‐checking and goodness‐of‐fit testing for the additive hazards model with case II interval‐censored data. We propose test statistics based on the supremum of the stochastic processes derived from the cumulative sum of martingale‐based residuals over time and covariates. We approximate the distribution of the stochastic process via a simulation technique to conduct a class of graphical and numerical techniques for various purposes of model‐fitting evaluations. Simulation studies are conducted to assess the finite‐sample performance of the proposed method. A real dataset from an AIDS observational study is analyzed for illustration.