This literature review had two objectives: to identify models for predicting the risk of coronary heart diseases in patients with diabetes (DM); and to assess model quality in terms of risk of bias (RoB) and applicability ...

This panel was made possible by the collaborative efforts of editors of Junctions and an intern from Transmission in Motion, both spaces being initiatives by Utrecht University. While emerging from independent curiosities ...

Meta-analysis techniques allow researchers to aggregate effect sizes—like standardized mean difference(s), correlation(s), or odds ratio(s)—of different studies. This leads to overall effect-size estimates and their ...

In dual system estimation and multiple system estimation problems there may be lists available that only cover subsets of the population by design. We discuss under which assumptions such structural undercoverage in the ...

Automatic text processing is now a mature discipline in computer science, and so attempts at advancements using quantum computation have emerged as the new frontier, often under the term of quantum natural language processing. ...

This study aims to investigate the day-of-the-week effect of cross-market leveraged exchange-traded funds (LETFs) in the Taiwanese stock market. We find that Wednesday's overnight returns are significantly positive for ...

Hidden Markov models (HMMs) are increasingly used to estimate and correct for classification error in categorical, longitudinal data, without the need for a “gold standard,” error-free data source. To accomplish this, HMMs ...

The promise of co-production is increased legitimacy, efficiency and effectiveness and the rise of digital technologies re-invigorates this promise. Often neglected in analyses of ICT-based co-production are public values, ...

In a broad range of fields it may be desirable to reuse a supervised classification algorithm and apply it to a new data set. However, generalization of such an algorithm and thus achieving a similar classification performance ...