Check mathematics papers: citations, claims and retractions

On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators

Chen, C., Ding, N., & Carin, L. (2016) · arXiv

Markov Chains and Monte Carlo MethodsStochastic Gradient Optimization Techniques

Cited by 106

Validation of prediction models in the presence of competing risks: a guide through modern methods

van Geloven, N., Giardiello, D., Bonneville, E. F., Teece, L., Ramspek, C. L., van Smeden, M., Snell, K. I. E., van Calster, B., Pohar-Perme, M., Riley, R. D., et al. (2022) · BMJ

Statistical Methods in EpidemiologyStatistical Methods and Inference

Cited by 106

A Gentle Introduction to the Comparison Between Null Hypothesis Testing and Bayesian Analysis: Reanalysis of Two Randomized Controlled Trials

Bendtsen, M. (2018) · Journal of Medical Internet Research

Statistical Methods and Bayesian InferenceStatistical Methods in Clinical Trials

Cited by 105

Forecasting covid-19 new cases using deep learning methods

Xu, L., Magar, R., & Barati Farimani, A. (2022) · Computers in Biology and Medicine

COVID-19 epidemiological studiesStock Market Forecasting Methods

Cited by 105

Marginal mean weighting through stratification: A generalized method for evaluating multivalued and multiple treatments with nonexperimental data

Hong, G. (2012) · Psychological Methods

Advanced Causal Inference TechniquesStatistical Methods and Bayesian Inference

Cited by 105

Must psychologists change the way they analyze their data?

Bem, D. J., Utts, J., & Johnson, W. O. (2011) · Journal of Personality and Social Psychology

Statistical Methods and Bayesian InferenceMeta-analysis and systematic reviews

Cited by 105

Continuous and Discontinuous Piecewise-Smooth One-Dimensional Maps: Invariant Sets and Bifurcation Structures

Avrutin, V., Gardini, L., Sushko, I., & Tramontana, F. (2019) · World Scientific Series on Nonlinear Science Series A

Mathematical Dynamics and FractalsAdvanced Differential Equations and Dynamical Systems

Cited by 105

Estimating SARS-CoV-2 infections from deaths, confirmed cases, tests, and random surveys

Irons, N. J., & Raftery, A. E. (2021) · Proceedings of the National Academy of Sciences

COVID-19 epidemiological studiesMathematical and Theoretical Epidemiology and Ecology Models

Cited by 105

A systematic review and meta-analysis estimating the expected dropout rates in randomized controlled trials on yoga interventions

Cramer, H., Haller, H., Dobos, G., & Lauche, R. (2016) · Evidence-based Complementary and Alternative Medicine

Statistical Methods in Clinical TrialsMeta-analysis and systematic reviews

Cited by 105

Estimation of the fraction of COVID-19 infected people in U.S. states and countries worldwide

Noh, J., & Danuser, G. (2021) · PLOS ONE

COVID-19 epidemiological studiesData-Driven Disease Surveillance

Cited by 104

The Wild Bootstrap with a “Small” Number of “Large” Clusters

Canay, I. A., Santos, A., & Shaikh, A. M. (2021) · The Review of Economics and Statistics

Advanced Causal Inference TechniquesSpatial and Panel Data Analysis

Cited by 104

Markov Chain Monte Carlo Estimation of a Multiparameter Decision Model: Consistency of Evidence and the Accurate Assessment of Uncertainty

Ades, A. E., & Cliffe, S. (2002) · Medical Decision Making

Statistical Methods and Bayesian InferenceHealth Systems, Economic Evaluations, Quality of Life

Cited by 104

Distributions of oxygen, nutrient, and metabolic waste concentrations in multicellular spheroids and their dependence on spheroid parameters

Groebe, K., & Mueller-Klieser, W. (1991) · European Biophysics Journal

Mathematical Biology Tumor GrowthCancer, Hypoxia, and Metabolism

Cited by 104

Closing the gap: Efficacy of a tablet intervention to support the development of early mathematical skills in UK primary school children

Outhwaite, L. A., Gulliford, A., & Pitchford, N. J. (2017) · Computers & Education

Cognitive and developmental aspects of mathematical skillsMathematics Education and Teaching Techniques

Cited by 104

Individually Randomized Group Treatment Trials: A Critical Appraisal of Frequently Used Design and Analytic Approaches

Pals, S. L., Murray, D. M., Alfano, C. M., Shadish, W. R., Hannan, P. J., & Baker, W. L. (2008) · American Journal of Public Health

Statistical Methods in Clinical TrialsMeta-analysis and systematic reviews

Cited by 104

Should governments continue lockdown to slow the spread of covid-19?

Melnick, E. R., & Ioannidis, J. P. A. (2020) · BMJ

COVID-19 epidemiological studiesCOVID-19 Prevention and Impact

Cited by 104

Nothing to See Here? A non-inferiority approach to parallel trends

Bilinski, A., & Hatfield, L. A. (2018) · arXiv

Advanced Causal Inference TechniquesStatistical Methods in Clinical Trials

Cited by 104

Estimation of Controlled Direct Effects

Goetgeluk, S., Vansteelandt, S., & Goetghebeur, E. (2008) · Journal of the Royal Statistical Society Series B: Statistical Methodology

Advanced Causal Inference TechniquesStatistical Methods in Epidemiology

Cited by 104

A flexible, interpretable framework for assessing sensitivity to unmeasured confounding

Dorie, V., Harada, M., Carnegie, N. B., & Hill, J. (2016) · Statistics in Medicine

Advanced Causal Inference TechniquesStatistical Methods and Bayesian Inference

Cited by 104

On tests of equivalence via non-unity relative risk for matched-pair design

Tang, N., Tang, M., & Chan, I. S. F. (2003) · Statistics in Medicine

Statistical Methods in Clinical TrialsStatistical Methods in Epidemiology

Cited by 104

Point Estimation of the Parameters of Piecewise Regression Models

Hawkins, D. M. (1976) · Applied Statistics

Statistical and numerical algorithmsStatistical Methods and Applications

Cited by 103

Empirical and counterfactual conditions for sufficient cause interactions

Vanderweele, T. J., & Robins, J. M. (2008) · Biometrika

Advanced Causal Inference TechniquesPhilosophy and History of Science

Cited by 103

Goodness-of-Fit Tests and Nonparametric Adaptive Estimation for Spike Train Analysis

Reynaud-Bouret, P., Rivoirard, V., Grammont, F., & Tuleau-Malot, C. (2014) · The Journal of Mathematical Neuroscience

Point processes and geometric inequalitiesStatistical Methods and Inference

Cited by 103

A comparison between bootstrap methods and generalized estimating equations for correlated outcomes in generalized linear models

Sherman, M., & Cessie, S. L. (1997) · Communications in Statistics - Simulation and Computation

Statistical Methods and Bayesian InferenceStatistical Methods and Inference

Cited by 103