相关论文: Contra-Analysis: Prioritizing Meaningful Effect Si…
Two broad positions within statistics define a treatment effect, on the one hand, as a parameter of a statistical model, and on the other, as an appropriate population-level difference in outcomes or counterfactual outcomes under the…
The two most used citation impact indicators in the assessment of scientific journals are, nowadays, the impact factor and the h-index. However, both indicators are not field normalized (vary heavily depending on the scientific category)…
Network meta-analysis is an evidence synthesis method for comparing the effectiveness of multiple available treatments. To justify evidence synthesis, consistency is an important assumption; however, existing methods founded on statistical…
Systematic reviews of interventions are important tools for synthesizing evidence from multiple studies. They serve to increase power and improve precision, in the same way that larger studies can do, but also to establish the consistency…
There are a number of measures of direct and indirect effects in the literature. They are suitable in some cases and unsuitable in others. We describe a case where the existing measures are unsuitable and propose new suitable ones. We also…
Equivalence testing compares the hypothesis that an effect $\mu$ is large against the alternative that it is negligible. Here, `large' is classically expressed as being larger than some `equivalence margin' $\Delta$. A longstanding problem…
Observational studies of treatment effects require adjustment for confounding variables. However, causal inference methods typically cannot deliver perfect adjustment on all measured baseline variables, and there is often ambiguity about…
Science is justly admired as a cumulative process ("standing on the shoulders of giants"), yet scientific knowledge is typically built on a patchwork of research contributions without much coordination. This lack of efficiency has…
In this paper, we propose a measure to assess scientific impact that discounts self-citations and does not require any prior knowledge on the their distribution among publications. This index can be applied to both researchers and journals.…
A/B tests serve the purpose of reliably identifying the effect of changes introduced in online services. It is common for online platforms to run a large number of simultaneous experiments by splitting incoming user traffic randomly in…
Clinical risk prediction is a valuable tool for guiding healthcare interventions toward those most likely to benefit. Yet, evaluating the pairing of a risk prediction model with an intervention using randomized controlled trials presents…
While methods for measuring and correcting differential performance in risk prediction models have proliferated in recent years, most existing techniques can only be used to assess fairness across relatively large subgroups. The purpose of…
Recently, importance of meta-analysis is increasing in the field of dentistry, since it is not easy to settle controversies arising from conflicting studies. Meta-analysis is the statistical method of combining results from two or more…
Systematic reviews aim to summarize all the available evidence relevant to a particular research question. If appropriate, the data from identified studies are quantitatively combined in a meta-analysis. Often only few studies regarding a…
The lack of predictability of citation-based measures frequently used to gauge impact, from impact factors to short-term citations, raises a fundamental question: Is there long-term predictability in citation patterns? Here, we derive a…
Identifying subgroups, which respond differently to a treatment, both in terms of efficacy and safety, is an important part of drug development. A well-known challenge in exploratory subgroup analyses is the small sample size in the…
For testing the statistical significance of a treatment effect, we usually compare between two parts of a population, one is exposed to the treatment, and the other is not exposed to it. Standard parametric and nonparametric two-sample…
In many countries and at European level, research policy increasingly focuses on 'excellent' researchers. The concept of excellence however is complex and multidimensional. For individual scholars it involves talents for innovative…
The development of scientometric indicators and methods for evaluative purposes, requires a multitude of assumptions, conventions, limitations, and caveats. Given this, we cannot permit ambiguities in the key concepts forming the basis of…
In modern scientific research, small-scale studies with limited participants are increasingly common. However, interpreting individual outcomes can be challenging, making it standard practice to combine data across studies using random…