Item positions in educational assessments are often randomized across students to prevent cheating. However, if altering item positions results in any significant impact on students' performance, it may threaten the validity of test scores. Two widely used approaches for detecting position effects -- logistic regression and hierarchical generalized linear modelling -- are often inconvenient for researchers and practitioners due to some technical and practical limitations. Therefore, this study introduced a structural equation modeling (SEM) approach for examining item and testlet position effects. The SEM approach was demonstrated using data from a computer-based alternate assessment designed for students with cognitive disabilities from three grade bands (3-5, 6-8, and high school). Item and testlet position effects were investigated in the field-test (FT) items that were received by each student at different positions. Results indicated that the difficulty of some FT items in grade bands 3-5 and 6-8 differed depending on the positions of the items on the test. Also, the overall difficulty of the field-test task in grade bands 6-8 increased as students responded to the field-test task in later positions. The SEM approach provides a flexible method for examining different types of position effects.