Check mathematics papers: citations, claims and retractions

Making Sense of Graphs: Critical Factors Influencing Comprehension and Instructional Implications

Friel, S. N., Curcio, F. R., & Bright, G. W. (2001) · Journal for Research in Mathematics Education

Statistics Education and MethodologiesMathematics Education and Teaching Techniques

Cited by 819

Total, Direct, and Indirect Effects in Logit and Probit Models

Breen, R., Karlson, K. B., & Holm, A. (2013) · Sociological Methods & Research

Advanced Causal Inference TechniquesStatistical Methods and Bayesian Inference

Cited by 818

Additive Combinatorics

Tao, T., & Vu, V. H. (2006) · Cambridge University Press eBooks

Limits and Structures in Graph TheoryAnalytic Number Theory Research

Cited by 816

Lessons learnt from easing COVID-19 restrictions: an analysis of countries and regions in Asia Pacific and Europe

Han, E., Tan, M. M. J., Turk, E., Sridhar, D., Leung, G. M., Shibuya, K., Asgari, N., Oh, J., García-Basteiro, A. L., Hanefeld, J., et al. (2020) · The Lancet

COVID-19 epidemiological studiesCOVID-19 Prevention and Impact

Cited by 814

Collider scope: when selection bias can substantially influence observed associations

Munafò, M. R., Tilling, K., Taylor, A. E., Evans, D. M., & Davey Smith, G. (2018) · International Journal of Epidemiology

Statistical Methods in EpidemiologyGenetic Associations and Epidemiology

Cited by 813

Models for Sample Selection Bias

Winship, C., & Mare, R. D. (1992) · Annual Review of Sociology

Advanced Causal Inference TechniquesStatistical Methods and Bayesian Inference

Cited by 812

Quantifying Biases in Causal Models: Classical Confounding vs Collider-Stratification Bias

Greenland, S. (2003) · Epidemiology

Advanced Causal Inference TechniquesStatistical Methods in Epidemiology

Cited by 810

Odds Ratios for Mediation Analysis for a Dichotomous Outcome

VanderWeele, T. J., & Vansteelandt, S. (2010) · American Journal of Epidemiology

Advanced Causal Inference TechniquesStatistical Methods in Epidemiology

Cited by 809

Modern modelling techniques are data hungry: a simulation study for predicting dichotomous endpoints

van der Ploeg, T., Austin, P. C., & Steyerberg, E. W. (2014) · BMC Medical Research Methodology

Statistical Methods in EpidemiologyArtificial Intelligence in Healthcare

Cited by 809

Revised standards for statistical evidence

Johnson, V. E. (2013) · Proceedings of the National Academy of Sciences

Statistical Methods and Bayesian InferenceMeta-analysis and systematic reviews

Cited by 808

Understanding controlled trials: Why are randomised controlled trials important?

Sibbald, B., & Roland, M. (1998) · BMJ

Statistical Methods in Clinical TrialsMeta-analysis and systematic reviews

Cited by 807

The simple difference formula: An approach to teaching nonparametric correlation

Kerby, D. S. (2014) · Comprehensive Psychology

Statistics Education and MethodologiesMeta-analysis and systematic reviews

Cited by 806

Mediation Models for Longitudinal Data in Developmental Research

Selig, J. P., & Preacher, K. J. (2009) · Research in Human Development

Advanced Causal Inference TechniquesStatistical Methods and Bayesian Inference

Cited by 804

Propensity score techniques and the assessment of measured covariate balance to test causal associations in psychological research.

Harder, V. S., Stuart, E. A., & Anthony, J. C. (2010) · Psychological Methods

Advanced Causal Inference TechniquesStatistical Methods and Bayesian Inference

Cited by 802

Accounting for missing data in statistical analyses: multiple imputation is not always the answer

Hughes, R. A., Heron, J., Sterne, J. A. C., & Tilling, K. (2019) · International Journal of Epidemiology

Statistical Methods and Bayesian InferenceAdvanced Causal Inference Techniques

Cited by 802

How Conditioning on Posttreatment Variables Can Ruin Your Experiment and What to Do about It

Montgomery, J. M., Nyhan, B., & Torres, M. (2018) · American Journal of Political Science

Advanced Causal Inference TechniquesEvaluation and Performance Assessment

Cited by 800

Evaluation of clinical prediction models (part 1): from development to external validation

Collins, G. S., Dhiman, P., Ma, J., Schlussel, M. M., Archer, L., Van Calster, B., Harrell, F. E., Martin, G. P., Moons, K. G. M., van Smeden, M., et al. (2024) · BMJ

Statistical Methods in EpidemiologyArtificial Intelligence in Healthcare

Cited by 798

Relation of pooled logistic regression to time dependent cox regression analysis: The framingham heart study

D'Agostino, R. B., Lee, M., Belanger, A. J., Cupples, L. A., Anderson, K., & Kannel, W. B. (1990) · Statistics in Medicine

Statistical Methods in EpidemiologyStatistical Methods and Inference

Cited by 798

Illustrating bias due to conditioning on a collider

Cole, S. R., Platt, R. W., Schisterman, E. F., Chu, H., Westreich, D., Richardson, D., & Poole, C. (2010) · International Journal of Epidemiology

Advanced Causal Inference TechniquesStatistical Methods in Epidemiology

Cited by 796

A Conditional Likelihood Ratio Test for Structural Models

Moreira, M. J. (2003) · Econometrica

Advanced Causal Inference TechniquesMonetary Policy and Economic Impact

Cited by 796

Random allocation software for parallel group randomized trials

Saghaei, M. (2004) · BMC Medical Research Methodology

Statistical Methods in Clinical TrialsAdvanced Causal Inference Techniques

Cited by 793

An investigation of the false discovery rate and the misinterpretation of p -values

Colquhoun, D. (2014) · Royal Society Open Science

Statistical Methods in Clinical TrialsMeta-analysis and systematic reviews

Cited by 792

Defining an Optimal Cut-Point Value in ROC Analysis: An Alternative Approach

Unal, I. (2017) · Computational and Mathematical Methods in Medicine

Statistical Methods in EpidemiologyImbalanced Data Classification Techniques

Cited by 789

Why inequality could spread COVID-19

Ahmed, F., Ahmed, N., Pissarides, C., & Stiglitz, J. (2020) · The Lancet Public Health

COVID-19 epidemiological studiesPublic Health and Social Inequalities

Cited by 788