The present study compared six methods, two of which utilize the content structure of items, to estimate total-test scores using 450 students and 60 items of the 110-item Stanford Mental Arithmetic Test. Three methods yielded fairly good estimates of the total-test score. (Author/RL)

This paper discusses the application of Hierarchical Linear Modeling (HLM) to the evaluation of the effectiveness of Basic Skills programs in the Newark (New Jersey) school district. Whether HLM is able to handle regression effects in Basic Skills examination data is studied. The analysis uses data from the Stanford Achievement Tests for…

The potential of a cognitive model task analysis scheme (CMS) that specifies features of test problems shown by research to affect performance is explored. CMS describes the general skill area and the generic task or problem type. It elaborates features of the problem situation and required responses found by research to influence performance.…

The feasibility of constructing composite scores which will yield pretest measures having all the properties required by the special regression model is explored as an alternative to the single pretest score usually used in student selection for Elementary Secondary Education Act Title I compensatory education programs. Reading data, including…

Item response data were obtained from large samples of students in Grades K-community college, taking the following tests: Stanford Early School Achievement Test, Stanford Achievement Test, Stanford Test of Academic Skills, Stanford Diagnostic Reading Test, and Stanford Diagnostic Mathematical Test. Data were classified as fitting or non-fitting…