Liu, Bowen2020-10-262020-10-262020-08https://hdl.handle.net/11299/216864University of Minnesota Ph.D. dissertation. 2020. Major: Educational Psychology. Advisor: Mark Davison. 1 computer file (PDF); viii, 128 pages.Dual-process theories of cognition, achievement, and social cognition can be modeled with three-dimensional branching models. In the reading assessment context, this research studied the question of whether it is possible to derive three dimensions (speed of reading, accuracy of a fast reading process, and accuracy of a slow reading process) that are both interpretable and empirically distinct. In the reading context, the fast process is called “automaticity,” a level of reading that may be necessary for the facile application of reading in further education and careers. Unless automaticity is attained, the effort of the reading process itself can interfere with comprehension and learning of reading content. Answering the questions about the distinctness of dual-process theory dimensions re-quired addressing a missing data problem found in earlier research on dual-process theories of intelligence and achievement. This study introduces the polytomous scoring method in dealing with missing data in branching models, specifically, Patrchev and De Boeck’s (2012) proposed branching model differentiating fast and slow intelligence. In the area of reading achievement, rather than intelligence, this study investigated the effect of missing values caused by a branch-ing model, and it proposes a polytomous scoring method as an alternative way to deal with missing values. The current study used a computer-administered reading comprehension assessment, which recorded students’ responses and response time for each item. In this study, both dichotomous and polytomous coding are discussed in the methodology section. All dichotomous variables were fitted with unidimensional and multidimensional 2PL models. Polytomous variables were fitted with unidimensional and multidimensional graded response models The results were compared with Patrchev and De Boeck’s (2012) research. The current study found the same result as did Patrchev and De Boeck’s (2012) research on model comparison in which three-dimensional models fit better than two-dimensional models. However, the theta correlations of three dimensions were different from their research. Raw scores were computed and used for validity evidence to aid the interpretation of latent dimensions.enThesis or Dissertation