A study of alternative approaches to non-normal latent trait distributions in item response theory models used for health outcome measurement.

It is often unrealistic to assume normally distributed latent traits in the measurement of health outcomes. If normality is violated, the item response theory (IRT) models that are used to calibrate questionnaires may yield parameter estimates that are biased. Recently, IRT models were developed for dealing with specific deviations from normality, such as zero-inflation (“excess zeros”) and skewness.

Differential item functioning of the PROMIS physical function, pain interference, and pain behavior item banks across patients with different musculoskeletal disorders and persons from the general population.

Purpose: To investigate the validity of comparisons across patients with different musculoskeletal disorders and persons from the general population by evaluating differential item functioning (DIF) for the PROMIS physical function (PROMIS-PF), pain interference (PROMIS-PI), and pain behavior (PROMIS-PB) item banks.

Methods: Patients with chronic pain, rheumatoid arthritis (RA), or osteoarthritis (OA); patients receiving physiotherapy (PT); and persons from the Dutch general population completed the full Dutch-Flemish PROMIS-PF (121-items), PROMIS-PI (40-items), or PROMIS-PB (39-items) banks. DIF was assessed with ordinal logistic regression models and McFadden's pseudo R-change of ≥ 2% as critical value.

Impact of spatial grouping on mean size estimation.

People represent summary statistics of visual scenes, but it is not fully clear whether such summary statistics are extracted automatically. To determine whether different levels of summary representation (i.e.