Combining Item Purification and Multiple Comparison Adjustment Methods in Detection of Differential Item Functioning.

Many of the differential item functioning (DIF) detection methods rely on a principle of testing for DIF item by item, while considering the rest of the items or at least some of them being DIF-free. Computational algorithms of these DIF detection methods involve the selection of DIF-free items in an iterative procedure called . Another aspect is the need to correct for multiple comparisons, which can be done with a number of existing methods.

Long-term cognitive trajectory and activities of daily living in healthy aging.

Objective: The purpose of the present study was to investigate if participants in NANOK study (National Normative Study of Cognitive Determinants of Healthy Ageing) who show no cognitive decline throughout five years (successful healthy agers; SHA) will show less age-related differences in instrumental activities of daily living (IADL) based on Functional Activities Questionnaire in comparison to participants who show subtle cognitive decline (Decliners) over time.

Method: We used two different classifications of SHA: Rogalski ( 25 SHA and  15 Decliners) based on cross-sectional neuropsychology measures and linear mixed model (LMEM; 20 SHA and 20 Decliners) based on the Montreal Cognitive Assessment longitudinal 5-years follow-up. Whole-brain T1- and T2-weighted images were corrected for distortions and segmented using Freesurfer.