161 real negative results, null findings, and replication failures in Mathematics. Search the index →
WASTE indexes published research — it does not host or republish full papers. Each entry is a metadata record compiled from open scholarly databases; the abstract is shown in full only where the paper is openly licensed, otherwise a short excerpt under fair use. Classifications are automated and approximate.
Murray G. Efford · 2026 · Ecology
Spatially explicit capture-recapture (SECR) methods are used widely to estimate animal population density and related parameters. Maximum likelihood has been applied to two flavors of the SECR model-a full model that includes absolute…
View details →Mathieu Guillaumé, Christine Schiltz, Amandine Van Rinsveld · 2020 · Journal of Numerical Cognition
Basic numerical abilities are generally assumed to influence more complex cognitive processes involving numbers, such as mathematics. Yet measuring non-symbolic number abilities remains challenging due to the intrinsic correlation between numerical and non-numerical dimensions of any visual scene. Several methods have been developed to generate non-symbolic stimuli controlling for the latter aspects but they tend to be difficult to replicate or implement. In this study, we describe the NASCO method, which is an extension to the method popularized by Dehaene, Izard, and Piazza (2005). Their pro
View details →Cynthia C. Griffin, Joseph Calvin Gagnon, Maggie H. Jossi et al. · 2018 · Rural Special Education Quarterly
This study examined mathematics strategy instruction that primes the common underlying structures of word problems using explicit instruction in a rural elementary classroom with fourth- and fifth-grade students with and without…
View details →Kevin D. Floate, Paul C. Coghlin · 2010 · The Canadian Entomologist
Abstract Fluctuating asymmetries (FAs) are small random deviations between left- and right-side measurements of normally symmetrical traits in a given organism. Changes in FA have frequently been proposed as biomarkers for organisms…
View details →Fırat Soylu, David Raymond, Arianna Gutierrez et al. · 2018 · Journal of Numerical Cognition
The impact of fingers on numerical cognition has received a great deal of attention recently. One sub-set of these studies focus on the relation between finger gnosis (also called finger sense or finger gnosia), the ability to identify and individuate fingers, and mathematical development. Studies in this subdomain have reported mixed findings so far. While some studies reported that finger gnosis correlates with or predicts mathematics abilities in younger children, others failed to replicate these results. The current study explores the relationship between finger gnosis and two arithmetic o
View details →Àngels Colomé · 2018 · Quarterly Journal of Experimental Psychology
Larger distance effects in high math-anxious individuals (HMA) performing comparison tasks have previously been interpreted as indicating less precise magnitude representation in this population. A recent study by Dietrich, Huber, Moeller, and Klein limited the effects of math anxiety to symbolic comparison, in which they found larger distance effects for HMA, despite equivalent size effects. However, the question of whether distance effects in symbolic comparison reflect the properties of the magnitude representation or decisional processes is currently under debate. This study was designed t
View details →Abigail Bradshaw, Dorothy Bishop, Zoe Woodhead · 2019 · Quarterly Journal of Experimental Psychology
A deficit in interhemispheric transfer has been proposed as a neuropsychological theory of dyslexia. Interactions between the hemispheres during word recognition can be studied using the visual half-field paradigm. The well-established…
View details →Esra Yiğit, Fikri Gökpınar · 2010 · Communications Faculty Of Science University of Ankara Series A1Mathematics and Statistics
The classical F-test to compare several population means depends on the assumption of homogeneity of variance of the population and the normality. When these assumptions especially the equality of variance is dropped, the classical F-test fails to reject the null hypothesis even if the data actually provide strong evidence for it. This can be considered a serious problem in some applications, especially when the sample size is not large. To deal with this problem, a number of tests are available in the literature. In this study, the Brown-Forsythe, Weerahandiís Generalized F, Parametric Bootst
View details →David Hong, Yue Sheng, Edgar Dobriban · 2026 · Journal of the American Statistical Association
Principal component analysis (PCA) is a foundational tool in modern data analysis, and a crucial step in PCA is selecting the number of components to keep. However, classical selection methods (e.g., scree plots, parallel analysis, etc.)…
View details →Matthew A. Masten, Alexandre Poirier · 2026 · American Economic Review
We show that, depending on how the impact of omitted variables is measured, it can be substantially easier for omitted variables to flip coefficient signs than to drive them to zero. This behavior occurs with “Oster's delta” (Oster 2019a),…
View details →Christian Bokhove · 2022 · Educational Research and Evaluation
An article by Kim et al. from 2014 examined individual- and school-level variables affecting the information and communication technology (ICT) literacy level of Korean elementary school students, finding differential gender effects. In…
View details →Yong Li, Henry Sun, Zuoli Zhang · 2025 · Pharmaceutics
Background: Physiologically based pharmacokinetic (PBPK) modeling is a mathematical approach that integrates human physiological parameters with drug-specific characteristics (including both active pharmaceutical ingredients and excipients), and it has emerged as one of the core technologies for optimizing the efficiency and reliability of drug development. Methods: This study synthesizes applications of PBPK models in FDA-approved drugs (2020–2024), systematically analyzing model utilization frequency, indication distribution, application domains and choice of modeling platforms, to reveal th
View details →Joe V. Selby, Carolien C. H. M. Maas, Bruce Fireman et al. · 2025 · JAMA Network Open
Importance: The Predictive Approaches to Treatment Effect Heterogeneity (PATH) Statement of 2020 proposed predictive modeling for identifying heterogeneity in treatment effects (HTE) in randomized clinical trials (RCTs). It described 2 approaches: risk modeling, which develops a multivariable model predicting individual baseline risk of study outcomes and then examines treatment effects across strata of predicted risk, and effect modeling, which develops a model that directly predicts individual treatment effects using a variety of regression and machine learning methods. Objective: To identif
View details →Ezequiel Mauro, Tiago de Castro, Marcus Zeitlhoefler et al. · 2025 · Journal of Hepatology
BACKGROUND & AIMS: Non-proportional hazards (NPH) can lead to discrepancies between interim (IA) and final analyses (FA) in randomized controlled trials (RCTs) of hepatocellular carcinoma (HCC). We assessed the impact of NPH in pivotal HCC…
View details →Freya Pollington, Spiros Denaxas, Kezhi Li et al. · 2025 · Journal of the American Medical Informatics Association
OBJECTIVES: Increasingly, structured longitudinal electronic health records (EHRs) are being harnessed to predict risk of having present but as yet undetected disease by analyzing "patient trajectories." Trajectory studies explore clinical event associations, characterize disease trajectories, and enhance risk prediction. This scoping review assesses study characteristics and objectives, identifies model types, and appraises model performance and reporting. MATERIALS AND METHODS: We conducted a scoping review, focused on a PubMed and Web of Science search for studies using temporal EHR sequenc
View details →Alessandro Arsie, Emilio Frazzoli · 2006 · arXiv
In this paper we consider a class of dynamic vehicle routing problems, in which a number of mobile agents in the plane must visit target points generated over time by a stochastic process. It is desired to design motion coordination strategies in order to minimize the expected time between the appearance of a target point and the time it is visited by one of the agents. We propose control strategies that, while making minimal or no assumptions on communications between agents, provide the same level of steady-state performance achieved by the best known decentralized strategies. In other words
View details →Karunia Putra Wijaya, Dipo Aldila · 2017 · arXiv
Investigating the seasonality of disease incidences is very important in disease surveillance in regions with periodical climatic patterns. In lieu of the paradigm about disease incidences varying seasonally in line with meteorology, this work seeks to determine how well standard epidemic models can capture such seasonality for better forecasts and optimal futuristic interventions. Once incidence data are assimilated by a periodic model, asymptotic analysis in relation to the long-term behavior of the disease occurrences can be performed using the classical Floquet theory, which explains the s
View details →Peter Bürgisser · 2022 · arXiv
Consider a system $f_1(x)=0,\ldots,f_n(x)=0$ of $n$ random real polynomials in $n$ variables, where each $f_i$ has a prescribed set of exponent vectors described by a set $A_i \subseteq \mathbb{Z}^n$ of cardinality $t_i$, whose convex hull is denoted $P_i$. Assuming that the coefficients of the $f_i$ are independent standard Gaussian, we prove that the expected number of zeros of the random system in the positive orthant is at most $(2π)^{-\frac{n}{2}} V_0 (t_1-1)\ldots (t_n-1)$. Here $V_0$ denotes the number of vertices of the Minkowski sum $P_1+\ldots + P_n$. However, this bound does not imp
View details →Aihua Xia, Fuxi Zhang · 2011 · arXiv
Random events in space and time often exhibit a locally dependent structure. When the events are very rare and dependent structure is not too complicated, various studies in the literature have shown that Poisson and compound Poisson processes can provide adequate approximations. However, the accuracy of approximations does not improve or may even deteriorate when the mean number of events increases. In this paper, we investigate an alternative family of approximating point processes and establish Stein's method for their approximations. We prove two theorems to accommodate respectively the po
View details →Nicolas Dupin · 2019 · arXiv
The discrete unit commitment problem with min-stop ramping constraints optimizes the daily production of thermal power plants (coal, gas, fuel units). For this problem, compact Integer Linear Programming (ILP) formulations have been designed to solve exactly small instances and heuristically real-size instances. This paper investigates whether Dantzig-Wolfe reformulation allows to improve the previous exact method and matheuristics. The extended ILP formulation is presented with the column generation algorithm to solve its linear relaxation. The experimental results show that the Dantzig-Wolfe
View details →Gilles Chardon · 2014 · arXiv
The scattering of waves by obstacles in a 2D setting is considered, in particular the computation of the scattered field via the collocation or the least-squares methods. In the case of multiple scattering by smooth obstacles, we prove that the scattered field can be uniformly approximated by sums of multipoles. For a unique obstacle, the choice of the number of points and their positions for the estimation of the error on the border of the scatterer is studied, showing the benefit of using a non-uniform distribution of points dependent on the scatterer and the approximation scheme. In general
View details →Nicolas Burq, Nicolas Camps, Mickaël Latocca et al. · 2024 · arXiv
We consider the Wick ordered cubic Schrödinger equation (NLS) posed on the two-dimensional sphere, with initial data distributed according to a Gaussian measure. We show that the second Picard iteration does not improve the regularity of the initial data in the scale of the classical Sobolev spaces. This is in sharp contrast with the Wick ordered NLS on the two-dimensional tori, a model for which we know from the work of Bourgain that the second Picard iteration gains one half derivative. Our proof relies on identifying a singular part of the nonlinearity. We show that this singular part is re
View details →Alexander Tolmachev · 2024 · arXiv
Determining the maximal density $m_1(\mathbb{R}^2)$ of planar sets without unit distances is a fundamental problem in combinatorial geometry. This paper investigates lower bounds for this quantity. We introduce a novel approach to estimating $m_1(\mathbb{R}^2)$ by reformulating the problem as a Maximal Independent Set (MIS) problem on graphs constructed from flat torus, focusing on periodic sets with respect to two non-collinear vectors. Our experimental results, supported by theoretical justifications of proposed method, demonstrate that for a sufficiently wide range of parameters this approa
View details →Martina Zizza · 2024 · arXiv
In this paper we examine the discrete Shnirelman's inequality [Shnirelman A., 1985], which relates the $L^2$-distance of two discrete configurations of a fluid to the $L^1_tL^2_x$-norm of the vector field connecting them. Our proof is inspired by [Shnirelman A., 1985], where it was obtained $α=\frac{1}{64}$ in dimension $ν=2$, while here we get $α\geq\frac{2}{7}$. Moreover we prove that $α\geq\frac{1}{ν+1}$ for any dimension $ν\geq 3$. We point out that, even if this does not improve the bound in the continuous version, where it was proved that $α\geq\frac{2}{4+ν}$, with $ν\geq 3$, our bound i
View details →Subha Maity, Debarghya Mukherjee, Mikhail Yurochkin et al. · 2020 · arXiv
Many instances of algorithmic bias are caused by subpopulation shifts. For example, ML models often perform worse on demographic groups that are underrepresented in the training data. In this paper, we study whether enforcing algorithmic fairness during training improves the performance of the trained model in the \emph{target domain}. On one hand, we conceive scenarios in which enforcing fairness does not improve performance in the target domain. In fact, it may even harm performance. On the other hand, we derive necessary and sufficient conditions under which enforcing algorithmic fairness l
View details →Hao Luo, Alexandre Bouchard-Côté, Gabriela Cohen Freue et al. · 2016 · arXiv
We extend the constrained maximum likelihood estimation theory for parameters of a completely identified model, proposed by Aitchison and Silvey (1958), to parameters arising from a partially identified model. With a partially identified model, some parameters of the model may only be identified through constraints imposed by additional assumptions. We show that, under certain conditions, the constrained maximum likelihood estimator exists and locally maximize the likelihood function subject to constraints. We then study the asymptotic distribution of the estimator and propose a numerical algo
View details →Mark Rubin · 2020 · arXiv
Preregistration entails researchers registering their planned research hypotheses, methods, and analyses in a time-stamped document before they undertake their data collection and analyses. This document is then made available with the published research report to allow readers to identify discrepancies between what the researchers originally planned to do and what they actually ended up doing. This historical transparency is supposed to facilitate judgments about the credibility of the research findings. The present article provides a critical review of 17 of the reasons behind this argument.
View details →Anh-Huy Phan, Petr Tichavský, Andrzej Cichocki · 2017 · arXiv
In CANDECOMP/PARAFAC tensor decomposition, degeneracy often occurs in some difficult scenarios, e.g., when the rank exceeds the tensor dimension, or when the loading components are highly collinear in several or all modes, or when CPD does not have an optimal solution. In such the cases, norms of some rank-1 terms become significantly large and cancel each other. This makes algorithms getting stuck in local minima while running a huge number of iterations does not improve the decomposition. In this paper, we propose an error preservation correction method to deal with such problem. Our aim is
View details →Andrea Schioppa · 2015 · arXiv
For each $β>1$ we construct a family $F_β$ of metric measure spaces which is closed under the operation of taking weak-tangents (i.e.~blow-ups), and such that each element of $F_β$ admits a $(1,P)$-Poincaré inequality if and only if $P>β$.
View details →Mark Rubin · 2024 · arXiv
One justification for preregistering research hypotheses, methods, and analyses is that it improves the transparent evaluation of the severity of hypothesis tests. In this article, I consider two cases in which preregistration does not improve this evaluation. First, I argue that, although preregistration may facilitate the transparent evaluation of severity in Mayo's error statistical philosophy of science, it does not facilitate this evaluation in Popper's theory-centric approach. To illustrate, I show that associated concerns about Type I error rate inflation are only relevant in the error
View details →