A5006196578- Scientific Computing and Data Management
- Biosensors and Analytical Detection
- Data Analysis with R
- Research Data Management Practices
- Distributed and Parallel Computing Systems
- Environmental Monitoring and Data Management
- Image Retrieval and Classification Techniques
- AI-based Problem Solving and Planning
- Manufacturing Process and Optimization
- SARS-CoV-2 detection and testing
- Biomedical Text Mining and Ontologies
- Semantic Web and Ontologies
- Intergenerational and Educational Inequality Studies
- Digital Imaging for Blood Diseases
- Spatial and Panel Data Analysis
- Additive Manufacturing and 3D Printing Technologies
- Advanced biosensing and bioanalysis techniques
- Marriage and Sexual Relationships
- Congenital heart defects research
- Diverse Scientific and Engineering Research
- Zebrafish Biomedical Research Applications
- Bayesian Methods and Mixture Models
- Statistical Methods and Applications
- Advanced Statistical Methods and Models
- Female Genital Mutilation/Cutting Issues
Chan Zuckerberg Initiative (United States)
2023-2024
University of Bristol
2012-2016
University of Cambridge
1998-2000
Royal College of Surgeons of England
1984
We illustrate how to fit multilevel models in the <b>MLwiN</b> package seamlessly from within Stata using program <code>runmlwin</code>. argue that and combination allows researchers capitalize on best features of both packages. provide examples use <code>runmlwin</code> continuous, binary, ordinal, nominal mixed response by maximum likelihood Markov chain Monte Carlo estimation.
Applications of multilevel models to continuous outcomes nearly always assume constant residual variance and random effects variances covariances. However, modeling heterogeneity can prove a useful indicator model misspecification, in some educational behavioral studies, it may even be direct substantive interest. The purpose this article is review, describe, illustrate set recent extensions two-level that allow the variance–covariance components specified as functions predictors. These...
Luminescence is ubiquitous in biology research and medicine. Conceptually simple, the detection of luminescence nonetheless faces technical challenges because relevant signals can exhibit exceptionally low radiant power densities. Although light well-established centralized laboratory settings, cost, size, environmental requirements high-performance benchtop luminometers are not compatible with geographically-distributed global health studies or resource-constrained settings. Here we present...
Malaria diagnostic testing in high transmission settings remains a burden on healthcare systems. Here we present Remoscope, portable automated imaging cytometer that scans fresh, unstained whole blood using custom neural network low-cost hardware. By screening up to two million red cells, Remoscope performs label-free quantitative stage-specific detection of
Abstract Luminescence is ubiquitous in biology research and medicine. Conceptually simple, the detection of luminescence nonetheless faces technical challenges because relevant signals can exhibit exceptionally low radiant power densities. Although light well-established centralized laboratory settings, cost, size, environmental requirements high-performance benchtop luminometers are not compatible with geographically-distributed global health studies or resource-constrained settings. Here...