Articles tagged with Statistical Methods
Comprehensive exploration of living organisms, biological systems, and life processes across all scales from molecules to ecosystems. Encompasses cutting-edge research in biology, genetics, molecular biology, ecology, biochemistry, microbiology, botany, zoology, evolutionary biology, genomics, and biotechnology. Investigates cellular mechanisms, organism development, genetic inheritance, biodiversity conservation, metabolic processes, protein synthesis, DNA sequencing, CRISPR gene editing, stem cell research, and the fundamental principles governing all forms of life on Earth.
Comprehensive medical research, clinical studies, and healthcare sciences focused on disease prevention, diagnosis, and treatment. Encompasses clinical medicine, public health, pharmacology, epidemiology, medical specialties, disease mechanisms, therapeutic interventions, healthcare innovation, precision medicine, telemedicine, medical devices, drug development, clinical trials, patient care, mental health, nutrition science, health policy, and the application of medical science to improve human health, wellbeing, and quality of life across diverse populations.
Comprehensive investigation of human society, behavior, relationships, and social structures through systematic research and analysis. Encompasses psychology, sociology, anthropology, economics, political science, linguistics, education, demography, communications, and social research methodologies. Examines human cognition, social interactions, cultural phenomena, economic systems, political institutions, language and communication, educational processes, population dynamics, and the complex social, cultural, economic, and political forces shaping human societies, communities, and civilizations throughout history and across the contemporary world.
Fundamental study of the non-living natural world, matter, energy, and physical phenomena governing the universe. Encompasses physics, chemistry, earth sciences, atmospheric sciences, oceanography, materials science, and the investigation of physical laws, chemical reactions, geological processes, climate systems, and planetary dynamics. Explores everything from subatomic particles and quantum mechanics to planetary systems and cosmic phenomena, including energy transformations, molecular interactions, elemental properties, weather patterns, tectonic activity, and the fundamental forces and principles underlying the physical nature of reality.
Practical application of scientific knowledge and engineering principles to solve real-world problems and develop innovative technologies. Encompasses all engineering disciplines, technology development, computer science, artificial intelligence, environmental sciences, agriculture, materials applications, energy systems, and industrial innovation. Bridges theoretical research with tangible solutions for infrastructure, manufacturing, computing, communications, transportation, construction, sustainable development, and emerging technologies that advance human capabilities, improve quality of life, and address societal challenges through scientific innovation and technological progress.
Study of the practice, culture, infrastructure, and social dimensions of science itself. Addresses how science is conducted, organized, communicated, and integrated into society. Encompasses research funding mechanisms, scientific publishing systems, peer review processes, academic ethics, science policy, research institutions, scientific collaboration networks, science education, career development, research programs, scientific methods, science communication, and the sociology of scientific discovery. Examines the human, institutional, and cultural aspects of scientific enterprise, knowledge production, and the translation of research into societal benefit.
Comprehensive study of the universe beyond Earth, encompassing celestial objects, cosmic phenomena, and space exploration. Includes astronomy, astrophysics, planetary science, cosmology, space physics, astrobiology, and space technology. Investigates stars, galaxies, planets, moons, asteroids, comets, black holes, nebulae, exoplanets, dark matter, dark energy, cosmic microwave background, stellar evolution, planetary formation, space weather, solar system dynamics, the search for extraterrestrial life, and humanity's efforts to explore, understand, and unlock the mysteries of the cosmos through observation, theory, and space missions.
Comprehensive examination of tools, techniques, methodologies, and approaches used across scientific disciplines to conduct research, collect data, and analyze results. Encompasses experimental procedures, analytical methods, measurement techniques, instrumentation, imaging technologies, spectroscopic methods, laboratory protocols, observational studies, statistical analysis, computational methods, data visualization, quality control, and methodological innovations. Addresses the practical techniques and theoretical frameworks enabling scientists to investigate phenomena, test hypotheses, gather evidence, ensure reproducibility, and generate reliable knowledge through systematic, rigorous investigation across all areas of scientific inquiry.
Study of abstract structures, patterns, quantities, relationships, and logical reasoning through pure and applied mathematical disciplines. Encompasses algebra, calculus, geometry, topology, number theory, analysis, discrete mathematics, mathematical logic, set theory, probability, statistics, and computational mathematics. Investigates mathematical structures, theorems, proofs, algorithms, functions, equations, and the rigorous logical frameworks underlying quantitative reasoning. Provides the foundational language and tools for all scientific fields, enabling precise description of natural phenomena, modeling of complex systems, and the development of technologies across physics, engineering, computer science, economics, and all quantitative sciences.
Stuart J. Pocock, a renowned statistician, will receive the TCT Career Achievement Award for his groundbreaking work in interventional cardiology. His research has transformed patient care through evidence-based insights, improving survival and quality of life for heart disease patients worldwide.
Researchers developed AI models based on UNet and MobileNet architectures to analyze standardized abnormalities in CT images, accurately identifying object presence and confidence. These models achieved an absolute percentage error of less than 5 percent, comparable to human professionals.
A new study by Penn State researchers found that US honey bee colony loss is primarily related to parasitic mites, extreme weather events, and nearby pesticides. The study integrated multiple large datasets at different spatial and temporal resolutions to assess various potential stressors associated with colony collapse across the US.
The National Cancer Institute awards $10.5 million to USC's Division of Biostatistics to develop statistical methods for uncovering new risk factors associated with cancer by integrating large volumes of health, genomic, and exposure data. The project aims to provide new insights into complex biological processes and discoveries of nov...
A new statistical method called CLIMB provides a more efficient way to analyze genomic data across multiple conditions. The method combines principles from two traditional techniques, reducing computational intensity and producing biologically interpretable results.
A University of Washington study found that heat-related mortality is a current environmental public health problem in Washington state, even in temperate areas. The study analyzed deaths from 1980 to 2018 and found significant increases in mortality on days with high humidex values.
The Florida Summer Institute in Biostatistics and Data Science recruits students from underrepresented groups, providing a rigorous quantitative education. The program introduces college students to statistical methods and applications in biomedical research, highlighting health disparities and social drivers of health.
Researchers at King Abdullah University of Science & Technology (KAUST) have developed a more robust and realistic general method for dealing with wind-driven phenomena in geostatistical modeling, which promises to greatly improve the accuracy of pollutant dispersion prediction.
Xiu Yang, a 2022 NSF CAREER award recipient, is working on an algorithmic approach to model and overcome hardware errors in quantum computing. He aims to enable the technology to achieve its promise of unparalleled speed in solving complex problems.
A new study from Lund University reveals that the most common analytical method in population genetics is deeply flawed, leading to incorrect results and misconceptions about ethnicity and genetic relationships. The method has been used in hundreds of thousands of studies, including medical genetics and commercial ancestry tests.
A new study from Lund University reveals that PCA, a widely used statistical method in population genetics, is deeply flawed. The method can produce flexible and unreliable results, leading to misconceptions about ethnicity and genetic relationships.
The program, one of only 18 nationwide, will support eight Ph.D. students and five postdoctoral fellows each year for five years, focusing on biomedical informatics and data science. The grant is the seventh renewal of support for a multidisciplinary training program that began over 30 years ago.
Researchers at Linköping University developed a new analysis model to estimate the number of wild animals harvested through hunting in Sweden. The model provides a better estimation of wild animal populations and reduces uncertainty, making it easier to track changes in ecosystems.
A recent paper by Darren Grant found favoritism in order assignment in various contests, including Texas and West Virginia primary elections. The author applied statistical methods to detect this behavior, which was often overlooked despite its significant impact on outcomes.
The study proposes a new statistical method to analyse population admixture, enabling more accurate determination of migration wave timing. The authors applied this method to Colombians and Mexicans, revealing two episodes of admixture in different time periods.
Researchers have successfully mapped the potential energy surfaces of individual water molecules in liquid water at room temperature and normal pressure. This breakthrough uses X-ray analysis and statistical modeling to reveal the complex behavior of water molecules, shedding light on their role as a solvent.
Researchers at the University of Barcelona have developed a new method to assess the antimicrobial efficacy of domestic cleaning products. The method, which has been presented to the European Committee for Standardisation, simulates domestic washing conditions and is more realistic and cost-effective than current protocols.
A new statistical method called Association Plot facilitates the determination and analysis of marker genes in single-cell data. This allows researchers to trace back RNA molecules to their cell of origin, providing insights into cell-type specific genes.
Researchers at NIST developed LANTERN, a new statistical tool that can predict protein function while providing interpretable explanations. The tool has shown promise in predicting genetic edits for COVID-19, E. coli, and GFP proteins, achieving high predictive accuracy.
A new study on bonobo social structure may hold clues to understanding human cooperation. Researchers found four neighboring groups of bonobos maintaining exclusive and stable borders, showing they interact regularly and peacefully with each other.
The CVIA journal has published its third issue of Volume 6, bringing together important research from China and the US. The issue includes papers on common statistical methods in medical research, as well as case summaries and studies on various cardiovascular topics.
A new statistical method for brain mapping is proposed to improve accuracy by removing redundant associations. The study uses simulations to test the method's performance on fake diseases and scores, revealing its superiority over existing approaches. The next step is to apply this refined analysis to study Alzheimer's disease.
A new method for detecting tsunamis using existing GPS satellites has been developed by an international team of researchers. The system can issue warnings within 15 minutes of an earthquake or tsunami, and can be implemented in countries with a sparse GPS network.
A recent study by Cornell scientists explores the relationship between human genetics and gut microbiome functions, identifying correlations between genetic variations and microbiome-associated traits. The research, led by Ilana Brito, uses a novel computational approach to model the distribution of functions and species within the hum...
A WVU researcher has developed new statistical methods for assessing airborne exposure to oil spill workers, allowing for more accurate estimates and consideration of undetectable levels. This research has significant implications for understanding the health effects of oil spills on workers.
Researchers found that opening stadiums to fans with safety protocols in place did not lead to an increase in local Covid case counts. The study used synthetic control method to analyze data from 16 stadiums, which mirrored the trajectory of surrounding counties without stadiums.
A new study by Thomas Pepinsky challenges the idea that language shapes thought and behavior, finding no evidence that linguistic differences affect social and economic outcomes. The study reveals that statistical methodologies used in previous research are prone to producing false positives.
Researchers at Tel Aviv University have developed a unique detector using compressed xenon gas to detect axion-like particles, promising a breakthrough in finding dark matter. The new technology enables the exploration of previously inaccessible masses, constraining the properties of axion-like particles.
Researchers at University of Illinois develop new method to accurately estimate soil organic carbon using airborne and satellite hyperspectral sensing. The study leverages machine learning algorithms with a comprehensive soil spectral library, enabling large-scale monitoring of surface soil organic carbon.
A team of researchers has made a breakthrough in understanding how the brain processes visual information by studying populations of neurons across multiple brain areas. The study reveals that feedforward and feedback signaling involve different neural activity patterns, shedding new light on how the brain communicates with itself.
KAUST researchers have developed a flexible statistical model to analyze environmental data, revealing niches where existing methods fall short. The study provides a new approach to modeling dependence structures, highlighting the importance of understanding model limitations and extrapolation beyond observed data.
A new study estimates that there are approximately 73,274 tree species on Earth, with 9,186 still to be discovered. This represents a 14% increase from previous estimates of 60,000 and 64,000 species. The majority of these undiscovered species are found in South America, highlighting the importance of forest conservation efforts.
A new model using Raman spectroscopy and chemometrics has been developed to accurately determine the post-mortem interval (PMI) in human skeletal remains. This non-destructive technique provides valuable information for forensic medicine and anthropology, improving reliability and accuracy.
Researchers at Boston University developed a real-time method for projecting COVID-19 quarantine needs in congregate housing settings ten days in advance. The team's findings were published in the American Journal of Public Health and can be used as a predictive tool to allocate resources.
A new statistical model has improved understanding of northern resident killer whale behaviors, revealing patterns in energy expenditure and prey capture. The enhanced hidden Markov model captures high-frequency information, providing insights into the whales' diving habits and conserving energy.
Researchers at Penn State developed a new risk score system that uses genetic data to predict obesity in young children. The scores, called polygenic risk scores, can be easily interpreted and have been shown to be effective in identifying children most at risk for developing obesity.
Researchers have developed a new statistical toolkit using the fragility index to determine if clinical trial results are strong and reliable. The new method has been shown to be more flexible than previous versions, allowing researchers to test assumptions and consider implications of a wider range of outcomes.
Researchers at Arizona State University have developed a new microscopy method that can track 100 single molecules simultaneously in three dimensions. The technique uses surface plasmon resonance (SPR) technology to precisely image molecular binding events and study their dynamic activities in real time.
A new data-model study suggests that the Antarctic Ice Sheet's tipping point was reached within a decade, leading to centuries of ice mass loss and potential irreversible ice retreat. The research team analyzed sediment cores and computer models to identify evidence of post-glacial tipping points in the past.
Climate scientists have identified abrupt transitions in ice core records using a new statistical method. The method analyzes the ratio of two oxygen isotopes to determine whether changes are due to noise or significant climactic shifts.
The study found that advances in iron metallurgy, horse riding, and agricultural productivity played a significant role in the development of military machines. Mega-empires emerged as societies supporting tens of millions of inhabitants and covering vast territories.
Researchers at Arizona State University have refined cryogenic electron microscopy to produce more accurate structures of biological samples. The new method uses a statistical approach to model transitory structures, which can play a vital role in biological processes.
A recent study by South Ural State University analyzed the relationship between informal employment and labor productivity in Russia. The researchers found that regions with high shares of informal employment experience volatile labor markets, which can negatively impact labor productivity and gross regional product.
QUT researchers developed a new mathematical model to enable faster solutions for complicated problems in agriculture, ecology and medicine. The method improves how to determine the 'best' intervention strategies, balancing benefits and side effects, and can be applied to farming practices and chemotherapy.
Lehigh University researchers are developing a model to understand the impact of grain growth on material properties. The project aims to create new materials informatics methods, innovative stochastic differential equations, and models of grain growth to improve material performance and reliability.
A new statistical model characterizes how ketamine anesthesia affects brain activity, including distinct states and transition patterns. This model provides a principled guide for anesthesiologists, neuroscientists, and data scientists to understand ketamine's effects on the brain.
Researchers used statistical models to study the co-evolutionary history of pierid butterflies and their host plants. They found that butterfly-plant relationships are resilient to changes in species composition but can destabilize over larger structural changes.
A new study analyzed Italian firms' Twitter conversations during the pandemic, revealing a focus on environmental sustainability and digital transformation. The research highlights the importance of corporate social responsibility and stakeholder engagement on these themes.
A new study led by George Mason University faculty Jenna Krall investigated how commuting patterns impact air pollution exposure, particularly fine particulate matter (PM2.5). The research found that commuters traveling during rush hour have higher overall exposure to traffic-related air pollution compared to sporadic commuters.
A new study developed methods to help breeders create fast-maturing soybean lines specifically for African environments. The researchers analyzed cultivar time-to-maturity against environmental variables and found daily minimum temperature and change in day length were more important than genotypic differences.
Researchers developed a new machine learning system to identify changes in biodiversity, including land clearing, despite cloud cover. The method accurately detected simulated land cover change under both clear felling and tree thinning, providing up-to-date predictions of missing data due to clouds.
Dr. Malene Hansen receives the Irving S. Wright Award for her work on cellular recycling and aging, while Dr. Morgan Levine wins the Vincent Cristofalo Rising Star Award for her biomarkers of aging research. Both awards recognize their contributions to advancing healthy aging through biomedical research.
Researchers developed a simple-to-use Multivariable Integrated Evaluation Tool (MVIETool) to facilitate climate model evaluation and models inter-comparison. The improved MVIE method provides a more comprehensive and precise evaluation of climate model performance, including accurate evaluation results for spatial fields.
A new computational method estimated that mass gatherings during the Malaysian election directly caused 70% of COVID-19 cases in Sabah and 64.4% elsewhere in Malaysia. The study used a synthetic control method to compare the aftermath of the election with what might have happened without the gatherings.
A new study by Hebrew University researcher Professor Barak Kol introduces a novel approach to the three-body problem, predicting the probability of each body escaping the system. The theory avoids infinite probabilities and provides strong agreement with computer simulations, indicating a paradigm shift in understanding the system.
Researchers found most British legal documents from this period were written on sheepskins, which allowed for easy detection of fraudulent changes. The high fat content of sheepskins made it difficult to alter text without leaving a visible mark.
Researchers at the University of Maryland have developed a cost-effective way to detect security threats in vehicle networks using graph-based anomaly detection techniques. This simple method requires less energy than machine learning or AI methods and can be easily adapted by car manufacturers.
The research project aims to share information and strategies with communities showing stress or decline to improve quality of life. The team will develop a Community Information Ecosystem to collect data on residents' perceptions of quality of life, which has remained stable or improved in shrinking small towns.
A recent study by a team of researchers from the University of Bologna has shed light on the Minoan system of fractions, revealing that the lowest fraction is 1/60. The results have significant implications for understanding the Linear B script and its use in measuring units of measurement.
A pilot study will examine the utility of quantitative ultrasound methods for assessing vaginal birth-induced pelvic floor injury and recovery in pregnant women. The researchers aim to develop noninvasive diagnostic methods that can predict long-term pelvic floor dysfunction.