Permutation, Parametric and Bootstrap Tests of Hypotheses

Permutation inference for the general linear model

Winkler, A. M., Ridgway, G. R., Webster, M. A., Smith, S. M., & Nichols, T. E. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.01.060 · Cited by 3,563 · see citing works

An introduction to recursive partitioning: Rationale, application, and characteristics of classification and regression trees, bagging, and random forests.

Strobl, C., Malley, J., & Tutz, G. (2009) · Psychological Methods · doi:10.1037/a0016973 · Cited by 2,583 · see citing works

Machine learning classifiers and fMRI: A tutorial overview

Pereira, F., Mitchell, T., & Botvinick, M. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.11.007 · Cited by 1,624 · see citing works

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls

Arbabshirani, M. R., Plis, S., Sui, J., & Calhoun, V. D. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.02.079 · Cited by 912 · see citing works

Testing the significance of a correlation with nonnormal data: Comparison of Pearson, Spearman, transformation, and resampling approaches.

Bishara, A. J., & Hittner, J. B. (2012) · Psychological Methods · doi:10.1037/a0028087 · Cited by 766 · see citing works

Automated Experiments on Ad Privacy Settings: A Tale of Opacity, Choice, and Discrimination

Datta, A., Tschantz, M. C., & Datta, A. (2015) · Proceedings on Privacy Enhancing Technologies · doi:10.1515/popets-2015-0007 · Cited by 676 · see citing works

Violating the normality assumption may be the lesser of two evils

Knief, U., & Forstmeier, W. (2021) · Behavior Research Methods · doi:10.3758/s13428-021-01587-5 · Cited by 654 · see citing works

Partial Least Squares Methods: Partial Least Squares Correlation and Partial Least Square Regression

Abdi, H., & Williams, L. J. (2013) · Methods in Molecular Biology · doi:10.1007/978-1-62703-059-5_23 · Cited by 448 · see citing works

Regional policy evaluation: interactive fixed effects and synthetic controls.

Gobillon, L., & Magnac, T. (2016) · Review of Economics and Statistics · doi:10.1162/rest_a_00537 · Cited by 424 · see citing works

Zero- vs. One-Dimensional, Parametric vs. Non-Parametric, and Confidence Interval vs. Hypothesis Testing Procedures in One-Dimensional Biomechanical Trajectory Analysis

Pataky, T. C., Vanrenterghem, J., & Robinson, M. A. (2015) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2015.02.051 · Cited by 385 · see citing works

Posttraumatic stress disorder is associated with an enhanced spontaneous production of pro-inflammatory cytokines by peripheral blood mononuclear cells

Gola, H., Engler, H., Sommershof, A., Adenauer, H., Kolassa, S., Schedlowski, M., Groettrup, M., Elbert, T., & Kolassa, I.-T. (2013) · BMC Psychiatry · doi:10.1186/1471-244x-13-40 · Cited by 225 · see citing works

Substantial reduction of naïve and regulatory T cells following traumatic stress

Sommershof, A., Aichinger, H., Engler, H., Adenauer, H., Catani, C., Boneberg, E.-M., Elbert, T., Groettrup, M., & Kolassa, I.-T. (2009) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2009.07.003 · Cited by 172 · see citing works

Which words are hard to recognize? Prosodic, lexical, and disfluency factors that increase speech recognition error rates

Goldwater, S., Jurafsky, D., & Manning, C. D. (2010) · Speech Communication · doi:10.1016/j.specom.2009.10.001 · Cited by 166 · see citing works

Non-invasive diagnosis of endometriosis based on a combined analysis of six plasma biomarkers

Mihalyi, A., Gevaert, O., Kyama, C. M., Simsa, P., Pochet, N., De Smet, F., De Moor, B., Meuleman, C., Billen, J., Blanckaert, N., et al. (2010) · Human Reproduction · doi:10.1093/humrep/dep425 · Cited by 161 · see citing works

Network Organization Unfolds over Time during Periods of Anxious Anticipation

McMenamin, B. W., Langeslag, S. J. E., Sirbu, M., Padmala, S., & Pessoa, L. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.1579-14.2014 · Cited by 140 · see citing works

A wild bootstrap approach for nonparametric repeated measurements

Friedrich, S., Konietschke, F., & Pauly, M. (2017) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2016.06.016 · Cited by 41 · see citing works

Analytical and biological variability in biomarker measurement in the hispanic community health study/study of latinos

Thyagarajan, B., Howard, A. G., Durazo-Arvizu, R., Eckfeldt, J. H., Gellman, M. D., Kim, R. S., Liu, K., Mendez, A. J., Penedo, F. J., Talavera, G. A., et al. (2016) · Clinica Chimica Acta · doi:10.1016/j.cca.2016.10.019 · Cited by 37 · see citing works

The exact equivalence of distance and kernel methods in hypothesis testing

Shen, C., & Vogelstein, J. T. (2021) · AStA Advances in Statistical Analysis · doi:10.1007/s10182-020-00378-1 · Cited by 41 · see citing works

Cardiac afferent activity modulates early neural signature of error detection during skilled performance

Bury, G., García-Huéscar, M., Bhattacharya, J., & Ruiz, M. H. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.04.043 · Cited by 20 · see citing works

Distribution-free uncertainty quantification for kernel methods by gradient perturbations

Csáji, B. C., & Kis, K. B. (2019) · Machine Learning · doi:10.1007/s10994-019-05822-1 · Cited by 12 · see citing works

Bandwidth-Optimal Random Shuffling for GPUs

Mitchell, R., Stokes, D., Frank, E., & Holmes, G. (2022) · ACM Transactions on Parallel Computing · doi:10.1145/3505287 · Cited by 6 · see citing works

Revisiting the Platonic Representation Hypothesis: An Aristotelian View

Gröger, F., Wen, S., & Brbić, M. (2026) · arXiv · doi:10.48550/arxiv.2602.14486