Differential item functioning (DIF) analyses have been used as the primary method in large-scale assessments to examine fairness for subgroups. Currently, DIF analyses are conducted utilizing manifest methods using observed characteristics (gender and race/ethnicity) for grouping examinees. Homogeneity of item responses is assumed denoting that…

In gender differential item functioning (DIF) research it is assumed that all members of a gender group have similar item response patterns and therefore generalizations from group level to subgroup and individual levels can be made accurately. However DIF items do not necessarily disadvantage every member of a gender group to the same degree,…

A first application of multilevel latent class analysis (MLCA) to educational large-scale assessment data is demonstrated. This statistical technique addresses several of the challenges that assessment data offers. Importantly, MLCA allows modeling of the often ignored teacher effects and of the joint influence of teacher and student variables.…

Numerous diagnostic studies have been conducted on large-scale assessments to illustrate the students' mastery profile in the areas of math and reading; however, for science a limited number of investigations are reported. This study investigated Iranian eighth graders' competency mastery of science and examined the utility of the General…