To address the scenario of testlet-based assessment, this research proposes a joint model of responses, response time, and answer change patterns for testlet-based cognitive diagnostic assessments. A simulation study was conducted to assess the impact of accounting for dual item and item time dependency and of incorporating answer change patterns as an additional data source on model fit, classification accuracy at the attribute and attribute profile level, and parameter estimation. Through manipulating three factors, the simulation study examined the extent to which the manipulated factors impacted the performance of the proposed model and two comparison models in recovering model parameters. Application of the proposed model was demonstrated with an empirical dataset.