In this paper the IRT project (Internet / Information Retrieval Tools) is described. The basic goal of IRT is to advise users of Internet search engines in retrieving information from the free public access part of the Internet. In achieving this, IRT has developed a model to evaluate search engines. This model is described in here. Evaluation criteria refer to functionality: search options, pr...

This introduction to the R package plink is a (slightly) modified version of Weeks (2010), published in the Journal of Statistical Software. The R package plink has been developed to facilitate the linking of mixed-format tests for multiple groups under a common item design using unidimensional and multidimensional IRT-based methods. This paper presents the capabilities of the package in the co...

The current paper describes new opportunities for patient-centred assessment methods which have come about by the increased adoption of affordable smart technologies in biopsychosocial research and medical care. In this commentary, we review modern assessment methods including item response theory (IRT), computer adaptive testing (CAT), and ecological momentary assessment (EMA) and explain how ...

An approach to essay grading based on signal detection theory (SDT) is presented. SDT offers a basis for understanding rater behavior with respect to the scoring of construct responses, in that it provides a theory of psychological processes underlying the raters’ behavior. The approach also provides measures of the precision of the raters and the accuracy of classifications. An application of ...

Using item response theory (IRT) in computer adaptive test (CAT) is critical to assess learners’ readiness for further learning. This theory has assumptions concerning the mathematical relationship between learner’s abilities and item responses. A numerical value from the theory has potential to decide who the best learner is. The IRT score only provides the learner’s result and lack of the ass...

Item Response Theory (IRT) allows for measuring ability of Machine Learning models as compared to a human population. However, it is difficult to create a large dataset to train the ability of deep neural network models (DNNs). We propose Crowd-Informed Fine-Tuning (CIFT) as a new training process, where a pre-trained model is fine-tuned with a specialized supplemental training set obtained via...

Infrared thermography (IRT) has shown to be an important non-destructive method for the investigation of cultural heritage. More specifically, active IRT, monitoring the evolution of emitted infrared radiation at the surface of a sample with time, provides information on the structure of the artefact as well as on the thermal properties of the constituting material. The technique has been appli...

Infrared thermal imaging (IRT) is a non-invasive, non-contact technique which allows one to measure and visualize infrared radiation. In medicine, thermal imaging has been used for more than 50 years in various clinical settings, including Raynaud's phenomenon and systemic sclerosis. Imaging and quantification of surface body temperature provides an indirect measure of the microcirculation's ov...

Infrared thermography (IRT) records the radiant heat of a body, which is emitted in the range of the electromagnetic spectrum that human vision is not able to identify. The thermal response depends on a number of specific physiological adjustments as body homeostasis and athlete’s health, which allow us to establishing interesting applications in sport. The aim of this study was to review the l...

In this paper a two-level regression model is imposed on the ability parameters in an IRT model. The advantage of using latent rather than observed scores as dependent variables of a multi-level model is that this offers the possibility of separating the influence of item difficulty and ability level and modeling response variation and measurement error. Another advantage is that, contrary to o...