Most cited mathematics papers
- Verified
Algorithms for nonnegative matrix and tensor factorizations: a unified view based on block coordinate descent framework
Kim, J., He, Y., & Park, H. (2014) · Journal of Global Optimization
Tensor decomposition and applicationsFace and Expression Recognition
Cited by 352
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On thinning of chains in MCMC
Link, W. A., & Eaton, M. J. (2012) · Methods in Ecology and Evolution
Markov Chains and Monte Carlo MethodsStatistical Methods and Bayesian Inference
Cited by 351
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Evidence for risk of bias in cluster randomised trials: review of recent trials published in three general medical journals
Puffer, S., Torgerson, D., & Watson, J. (2003) · BMJ
Statistical Methods in Clinical TrialsMeta-analysis and systematic reviews
Cited by 351
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Pharmacokinetic/Pharmacodynamic Modeling in Drug Development
Sheiner, L. B., & Steimer, J.-L. (2000) · Annual Review of Pharmacology and Toxicology
Statistical Methods in Clinical TrialsPharmaceutical studies and practices
Cited by 351
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Geometric quantization of Chern-Simons gauge theory
Axelrod, S., Della Pietra, S., & Witten, E. (1991) · Journal of Differential Geometry
Geometric and Algebraic TopologyAlgebraic structures and combinatorial models
Cited by 350
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Potential impact on estimated treatment effects of information lost to follow-up in randomised controlled trials (LOST-IT): systematic review
Akl, E. A., Briel, M., You, J. J., Sun, X., Johnston, B. C., Busse, J. W., Mulla, S., Lamontagne, F., Bassler, D., Vera, C., et al. (2012) · BMJ
Statistical Methods in Clinical TrialsMeta-analysis and systematic reviews
Cited by 350
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Two-way Fixed Effects Estimators with Heterogeneous Treatment Effects
de Chaisemartin, C., & D'Haultfoeuille, X. (2019) · National Bureau of Economic Research
Advanced Causal Inference TechniquesSpatial and Panel Data Analysis
Cited by 350
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Monotonicity of effect sizes: questioning kappa-squared as mediation effect size measure
Wen, Z., & Fan, X. (2015) · Psychological Methods
Advanced Causal Inference TechniquesMeta-analysis and systematic reviews
Cited by 350
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COVID-19 in New Zealand and the impact of the national response: a descriptive epidemiological study
Jefferies, S., French, N., Gilkison, C., Graham, G., Hope, V., Marshall, J., McElnay, C., McNeill, A., Muellner, P., Paine, S., et al. (2020) · The Lancet Public Health
COVID-19 epidemiological studiesCOVID-19 Prevention and Impact
Cited by 349
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A Critique of the Bayesian Information Criterion for Model Selection
WEAKLIEM, D. L. (1999) · Sociological Methods & Research
Statistical Methods and InferenceStatistical Methods and Bayesian Inference
Cited by 349
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Matching Methods for Causal Inference with Time‐Series Cross‐Sectional Data
Imai, K., Kim, I. S., & Wang, E. H. (2023) · American Journal of Political Science
Advanced Causal Inference TechniquesSpatial and Panel Data Analysis
Cited by 349
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The Problem With Composite End Points in Cardiovascular Studies
Kip, K. E., Hollabaugh, K., Marroquin, O. C., & Williams, D. O. (2008) · Journal of the American College of Cardiology
Statistical Methods in Clinical TrialsCoronary Interventions and Diagnostics
Cited by 348
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Statistical Literacy as a Goal for Introductory Statistics Courses
Rumsey, D. J. (2002) · Journal of Statistics Education
Statistics Education and MethodologiesScience Education and Pedagogy
Cited by 348
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Population time series: process variability, observation errors, missing values, lags, and hidden states.
Clark, J. S., & Bjørnstad, O. N. (2004) · Ecology
Mathematical and Theoretical Epidemiology and Ecology ModelsMarkov Chains and Monte Carlo Methods
Cited by 348
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Estimating average causal effects under general interference, with application to a social network experiment
Aronow, P. M., & Samii, C. (2017) · The Annals of Applied Statistics
Advanced Causal Inference TechniquesOptimal Experimental Design Methods
Cited by 347
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Total number of neurons and glial cells in human brain nuclei estimated by the disector and the fractionator
Pakkenberg, B., & Gundersen, H. J. G. (1988) · Journal of Microscopy
Point processes and geometric inequalitiesCell Image Analysis Techniques
Cited by 347
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Short-time fourier transform: two fundamental properties and an optimal implementation
Durak, L., & Arikan, O. (2003) · IEEE Transactions on Signal Processing
Mathematical Analysis and Transform MethodsSparse and Compressive Sensing Techniques
Cited by 345
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An Overview of CellML 1.1, a Biological Model Description Language
Cuellar, A. A., Lloyd, C. M., Nielsen, P. F., Bullivant, D. P., Nickerson, D. P., & Hunter, P. J. (2003) · SIMULATION
Modeling and Simulation SystemsGene Regulatory Network Analysis
Cited by 345
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Markov Chain Monte Carlo Simulations and Their Statistical Analysis: With Web-Based Fortran Code
Berg, B. A. (2004) · WORLD SCIENTIFIC eBooks
Markov Chains and Monte Carlo MethodsTheoretical and Computational Physics
Cited by 345
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Missing Data in Multiple Item Scales: A Monte Carlo Analysis of Missing Data Techniques
Roth, P. L., Switzer, F. S., & Switzer, D. M. (1999) · Organizational Research Methods
Statistical Methods and Bayesian InferencePsychometric Methodologies and Testing
Cited by 344
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Bayesian Measures of Explained Variance and Pooling in Multilevel (Hierarchical) Models
Gelman, A., & Pardoe, I. (2006) · Technometrics
Statistical Methods and Bayesian InferenceSpatial and Panel Data Analysis
Cited by 342
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What to believe: Bayesian methods for data analysis
Kruschke, J. K. (2010) · Trends in Cognitive Sciences
Statistical Methods and Bayesian InferenceBayesian Modeling and Causal Inference
Cited by 342
- Verified
Approximately Optimal One-Parameter Boundaries for Group Sequential Trials
Wang, S. K., & Tsiatis, A. A. (1987) · Biometrics
Statistical Methods in Clinical TrialsProbability and Statistical Research
Cited by 341
- Verified
Characterizations of an empirical influence function for detecting influential cases in regression
Cook, R. D., & Weisberg, S. (1980) · Technometrics
Advanced Statistical Methods and ModelsStatistical and numerical algorithms
Cited by 341
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