Missing item responses are prevalent in educational large-scale assessment studies such
as the programme for international student assessment (PISA). The current operational …

Large‐scale educational surveys are low‐stakes assessments of educational outcomes
conducted using nationally representative samples. In these surveys, students do not …

Data from competence tests usually show a number of missing responses on test items due
to both omitted and not-reached items. Different approaches for dealing with missing …

In recent literature, alternative models for handling missing item responses in large-scale
assessments are proposed. In principle, based on simulations and arguments based test …

Large-scale assessments (LSAs) use Mislevy's “plausible value”(PV) approach to relate
student proficiency to noncognitive variables administered in a background questionnaire …

Mechanisms causing item nonresponses in large-scale assessments are often said to be
nonignorable. Parameter estimates can be biased if nonignorable missing data mechanisms …

Missing responses resulting from omitted or not-reached items are beyond researchers'
control and potentially threaten the validity of test results. Empirical evidence concerning the …

In educational large-scale assessment (LSA) studies such as PISA, item response theory
(IRT) scaling models summarize students' performance on cognitive test items across …

Educational large-scale assessments (LSAs) often provide plausible values for the
administered competence tests to facilitate the estimation of population effects. This requires …

Unidimensionality and local independence are two common assumptions of item response
theory. The former implies that all items measure a common latent trait, while the latter …