An important step in scale development and assessment is to evaluate differential item
functioning (DIF) across segments of the population. Recent approaches use lasso …

In item response theory, uncertainty associated with estimated item parameters can lead to
greater uncertainty in subsequent analyses, such as estimating trait scores for individual …

When latent variables are used as outcomes in regression analysis, a common approach
that is used to solve the ignored measurement error issue is to take a multilevel perspective …

In item response theory (IRT), it is often necessary to perform restricted recalibration (RR) of
the model: A set of (focal) parameters is estimated holding a set of (nuisance) parameters …

The uncertainty arising from item parameter estimation is often not negligible and must be
accounted for when calculating latent variable (LV) scores in item response theory (IRT). It is …

It is widely believed that a joint factor analysis of item responses and response time (RT)
may yield more precise ability scores that are conventionally predicted from responses only …

Item response theory models and applications are affected by many sources of variability,
including errors associated with item parameter estimation. Metric stability analysis (MSA) is …

Two independent statistical tests of item compromise are presented, one based on the test
takers' responses and the other on their response times (RTs) on the same items. The tests …

In applications of item response theory (IRT), it is often of interest to compute confidence
intervals (CIs) for person parameters with prescribed frequentist coverage. The ubiquitous …

Recent advancements in testing differential item functioning (DIF) have greatly relaxed
restrictions made by the conventional multiple group item response theory (IRT) model with …