The framework and procedures of generalizability theory are introduced and illustrated in this instructional module that uses a hypothetical scenario involving writing proficiency. Generalizability analyses are useful for understanding the relative importance of various sources of error and for designing efficient measurement procedures. (SLD)

This paper discusses standard error of measurement (SEM), the amount of variation or spread in the measurement errors for a test, and gives information needed to interpret test scores using SEMs. SEMs at various score levels should be used in calculating score bands rather than a single SEM value. (SLD)