Results 101 to 110 of about 14,062,107 (346)
The consequences of ignoring measurement invariance for path coefficients in structural equation models [PDF]
, 2014 We report a Monte Carlo study examining the effects of two strategies for handling measurement non-invariance – modeling and ignoring non-invariant items – on structural regression coefficients between latent variables measured with item response theory ...
Guenole, Nigel +3 more
core +1 more source
On Item Response Theory models in allostatic load scoring
Comprehensive Psychoneuroendocrinology, 2021 Fausto Coutinho-Lourenço +2 more
doaj +1 more source
Investigating transcription factor dynamics in health and disease using FRAP
FEBS Letters, EarlyView.FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj +3 more
wiley +1 more source
Bayesian Estimation of MIRT Models with General and Specific Latent Traits in MATLAB [PDF]
Multidimensional item response models have been developed to incorporate a general trait and several specific trait dimensions. Depending on the structure of these latent traits, different models can be considered.
Yanyan Sheng
core
, 2018 Supplemental material, Online_Supplement for Assessing Item-Level Fit for Higher Order Item Response Theory Models by Xue Zhang, Chun Wang and Jian Tao in Applied Psychological ...
Chun Wang (337817) +2 more
core +1 more source
Educational Process: International JournalBackground/purpose. This study aimed to reveal the accuracy of estimation of multiple-choice test items parameters following the models of the item-response theory in measurement. Materials/methods.
Aiman Mohammad Freihat +1 more
doaj +1 more source
Psychological Test Adaptation and Development: We conducted two studies on using random forests (RFs) with explainable artificial intelligence (XAI) to detect differential item functioning (DIF) in multidimensional item response theory (MIRT) models.
Karoline Wolandt +1 more
doaj +1 more source
Modeling variability in item parameters in item response models
, 2001 In some areas of measurement item parameters should not be modeled as fixed but as random. Examples of such areas are: item sampling, computerized item generation, measurement with substantial estimation error in the item parameter estimates, and grouping of items under a common stimulus or in a common context.
Glas, Cornelis A.W. +1 more
openaire +1 more source
Microbiome‐blood–brain barrier interactions in aging — mechanisms and therapeutic potential
FEBS Letters, EarlyView.Aging reshapes the gut microbiome (↓SCFA‐producing commensals; ↑pro‐inflammatory outputs), shifting circulating metabolites (↓SCFAs; ↑LPS, ↑TMAO, ↑PAA) that act at the BBB to increase nonspecific transcytosis, alter transport, and promote astrocyte reactivity, heightening brain vulnerability.
Daniel Cuervo‐Zanatta +3 more
wiley +1 more source
Extended Rasch Modeling: The eRm Package for the Application of IRT Models in R [PDF]
Item response theory models (IRT) are increasingly becoming established in social science research, particularly in the analysis of performance or attitudinal data in psychology, education, medicine, marketing and other fields where testing is relevant ...
Patrick Mair, Reinhold Hatzinger
core