This study examined the role of domain-general and domain-specific linguistic knowledge in the assessment of academic English language proficiency using a latent variable modeling approach. The goal of the study was to examine if modeling of domain-specific variance results in improved model fit and well-defined latent factors. Analyses were carried out on data from the ACCESS for ELLs[R] test battery, which comprises multiple test forms targeting different grade and proficiency levels. The results of the study provide empirical evidence in support of the conceptual distinction of domain-specific and domain-general linguistic knowledge. Domain-specific factors tended to become more salient with increasing language proficiency, whereas the salience of domain-general factors tended to decrease. However, overall domain-general factors remained stronger than the domain-specific factors. In one test form targeting high levels of proficiency, this factor pattern was reversed, suggesting some degree of fluidity in the relationship between domain-general and domain-specific linguistic knowledge. (Contains 4 footnotes, 8 tables, and 3 figures.)