Misclassification in both the response variable and the covariate has received very limited attention in the literature. For situations where the response variable and the covariate are simultaneously subject to misclassification errors, often an assumption of independent misclassification errors is used without justification. The aim of our work is to show the harmful consequences of inappropriate adjustment for the joint misclassification errors, that is, ignoring the dependence between the misclassification process of the response variable and that of the covariate. Moreover, we propose likelihood ratio tests to check the nondifferential/independent misclassification assumption in main study/internal validation study designs. Our simulation studies indicate that only ignoring the dependent error structure can be even worse than ignoring all the misclassification errors when the validation data size is relatively small. We illustrate the methodology by a real data example.