26 papers · ranked by Valyu relevance
Ying Cao, Ronald C Chen, Aaron J Katz
A sample comprises the individuals from whom we collect data and represents a share of the population (N) for whom we want to draw conclusions (eg, women breast cancer). The sample size (n) is the number of individual people, experimental units, or other elements included in a sample, and is a central concept in…
D. Samuel Schwarzkopf, Zien Huang
Most studies in psychology, neuroscience, and life science research make inferences about how strong an effect is on average in the population. Yet, many research questions could instead be answered by testing for the universality of the phenomenon under investigation. By using reliable experimental designs that…
Anthony Steven Dick, Jonathan S. Comer, Mohammadreza Bayat, Marilyn Curtis + 6 more
The Adolescent Brain Cognitive Development (ABCD) Study represents a pioneering initiative that aims to unravel the complexities of behavioral and neural development in youth. In this paper, we address the challenges inherent in extracting meaningful insights from the extensive data compiled by the ABCD initiative. Our…
Selina Weiss, Lara S. Elmdust, Benjamin Goecke
In psychology, small sample sizes are a frequent challenge-particularly when studying specific expert populations or using complex and cost-intensive methods like human scoring of creative answers-as they reduce statistical power, bias results, and limit generalizability. They also hinder the use of frequentist…
Christopher Tyler
In the present era of big data analysis, there is a general sense that selective data reporting, ie, cherry-picking, data-peeking, or p-hacking in any form, is wrong and leads to false or misleading conclusions ([7]; [4]). Faced with a large dataset with numerous testable results, it is very tempting to seize on those…
Maren Hackenberg, Connor, Sophia G., Fabian Kabus + 11 more
The emergence of breakthrough artificial intelligence (AI) techniques has led to a renewed focus on how small data settings, i.e., settings with limited information, can benefit from such developments. This includes societal issues such as how best to include underrepresented groups in data-driven policy and decision…
John Heine, Erin E.E. Fowler, Anders Berglund, Michael J. Schell + 1 more
Proper data modeling in biomedical research requires sufficient data for exploration and reproducibility purposes. A limited sample size can inhibit objective performance evaluation. We are developing a synthetic population (SP) generation technique to address the limited sample size condition. We show how to estimate…
Carlos Vergara-Hernández, Marc Marí-Dell’Olmo, Laura Oliveras, Miguel A. Martínez‐Beneito
survey studies Authors: ['Carlos Vergara-Hernández' 'Marc Marí-Dell’Olmo' 'Laura Oliveras' 'Miguel A. Martínez‐Beneito'] Spatial small area estimation models have become very popular in some contexts, such as disease mapping. Data in disease mapping studies are exhaustive, that is, the available data are supposed to be…
Ibrahim Salay, Jagath Senarathne
Small sample sizes pose significant challenges in regression analysis, often leading to violations of classical assumptions such as normality, homoscedasticity, and independence of residuals. These violations compromise parameter estimation accuracy, reduce statistical power, and limit the generalizability of findings.…
Robin J. Boyd, Gary D. Powney, Oliver L. Pescott
In most circumstances, probability sampling is the only way to ensure unbiased inference about population quantities where a complete census is not possible. As we enter the era of "big data", however, nonprobability samples, whose sampling mechanisms are unknown, are undergoing a renaissance. We explain why the use of…
Hongli Jiang, S. Hessam M. Mehr
The availability, portability, and low cost of electronic devices have made them a prime candidate for the rapid detection of chemical particles. Here we designed a chemical particle detection system based on a Raspberry Pi camera to detect micron droplets generated by ultrasonic atomizers. Through the analysis of…
Crispin Jordan, Nicola Romanò, John Menzies
All in vivo studies using laboratory animals should be guided by the Three Rs: Replacement, Reduction and Refinement. The concept of Reduction is important in sample size estimation; the sample size used should allow the detection of a biologically meaningful effect size using appropriate statistical tests, but not at…
Authors not listed
Introduction: Blood microsampling (BµS) devices collect less than 100 µL of blood, offering a less invasive and more cost-effective alternative to venipuncture. However, its metabolomic comparability to conventional samples remains unclear, and standardized BµS metabolomic workflows are lacking. Objectives: This study…
Authors not listed
Early-stage drug discovery often suffers from data scarcity and out-of-distribution (OOD) shifts, which constrain the reliability of predictive models. While deep learning has advanced representation learning from molecular and biological data, tabular modeling remains indispensable, particularly in small-sample and…
Ben O’Neill, Zhongxue Chen
We analyse standard confidence intervals for the mean of a finite population, with a view to sample size determination. We first consider a standard method for sample size determination based on the assumption of knowledge of the population variance parameter. We then consider the more realistic case where the…
Henrique Bravo, Yacine Ben Chehida, Sancia E.T. van der Meij
Species’ occurrence rates are the backbone of many ecological studies. Sampling of species occurrence, however, can come with challenges and might prove more difficult than anticipated. Logistical difficulties, limited funds or time, elusiveness or rarity of species and difficult sampling environments are all examples…
Piero Demetrio Falorsi, Stefano Falorsi, Vincenzo Nardelli, Paolo Righi
'Paolo Righi'] Abstract. The paper delineates a proper statistical setting for defining the sampling design for a small area estimation problem. This problem is often treated only via indirect estimation using the values of the variable of interest also from different areas or different times, thus increasing the…
Alaa Althubaiti
Although sample size calculations play an essential role in health research, published research often fails to report sample size selection. This study aims to explain the importance of sample size calculation and to provide considerations for determining sample size in a simplified manner. Approaches to sample size…
Erin M. Buchanan, Mahmoud M. Elsherif, Jason Geller, Chris L. Aberson + 21 more
The planning of sample size for research studies often focuses on obtaining a significant result given a specified level of power, significance, and an anticipated effect size. This planning requires prior knowledge of the study design and a statistical analysis to calculate the proposed sample size. However, there may…
Robert Montgomery
Pilot and feasibility studies are crucial for determining whether follow-up trials should be conducted. To be effective, these studies need to be properly designed and have large enough samples to make correct decisions about proceeding to a future trial at a high rate. However, there is significantly less clarity…
Erkan Buzbas, Berna Devezer
A core problem that has been addressed in the scientific reform movement so far is the low rates of reproducibility of research results. Mainstream reform literature aimed at increasing reproducibility rates by implementing changes in research practice and scientific policy. At the sidelines of reform, theoreticians…
Charles W. Champ, Andrew V. Sills
A case is made that researchers are interested in studying processes. Often the inferences they are interested in making are about the process and its associated population. On other occasions, a researcher may be interested in making an inference about the collection of individuals the process has generated. We will…
Jae Kwang Kim
This textbook on survey sampling has its origins in a set of lecture notes prepared for a course on survey sampling at Iowa State University. Over the years, these notes have been refined and expanded into the comprehensive volume you now hold. It is designed to serve both as an introductory text for students and as a…
Matthew Lewis, Elena Chekmeneva, Stephane Camuzeaux, Caroline Sands + 11 more
Metabolomics utilising liquid chromatography mass spectrometry (LC-MS) offers biomedical researchers a powerful means of assessing and comparing human phenotypes via measurement of the metabolome in biological samples. Platforms for LC-MS-based global profiling quantify hundreds or thousands of small molecule…
Authors not listed
Accurate and efficient calculation of alchemical free energies is a critical challenge in computational chemistry, frequently hindered by the inherent limitations of conventional Thermodynamic Integration (TI) methods. These limitations include poor phasespace overlap between discrete alchemical states, inefficient…
María José Navarrete Méndez, Amanda B. Quezada Riera, Andrea Terán-Valdez, Elena Naydenova + 2 more
Non-lethal sampling methods are increasingly essential for amphibian research as global declines intensify and many species persist in small, vulnerable populations. Skin biopsies offer a promising alternative to whole-animal collection and other minimally invasive approaches; however, systematic evaluations of…