Nathaniel E. Helwig University of Minnesota

Associate Professor of Psychology and Statistics

Nathaniel E. Helwig's Google Scholar citations by year.

Peer-Reviewed Journal Articles:


  1. Lee, J. W., & Helwig, N. E. (2026). Classifying alcoholism from electroencephalography data using high-dimensional penalized regression. Proceedings of the 90th Annual International Meeting of the Psychometric Society, Minneapolis, Minnesota, United States. doi: 10.64028/imps2025.Sl2ZU8W0Gq
  2. Helwig, N. E., Chen K., Guy S. J., & Lyford-Pike S. (2026) Regularized multilevel multinomial regression for select-all-that-apply responses and high-dimensional predictors with applications to perception of facial expressions. Psychometrika, 91(3), 868-888. doi: 10.1017/psy.2026.10102
  3. Kage, C. C., Abbott, R. E., MacEwen, M., Ladd, B., Haselhuhn, J., Sembrano, J., Helwig, N. E., Ellingson, A. M. (2026). Altered cervical intervertebral motion in chronic neck pain: evidence from biplane videoradiography. Journal of Electromyography and Kinesiology, 89, 103163. doi: 10.1016/j.jelekin.2026.103163
  4. Delgado, J. E., Elison, J. T., & Helwig, N. E. (2026). Robust detection of signed outliers in multivariate data with applications to early identification of risk for autism. Psychological Methods, 31(1), 158-173. doi: 10.1037/met0000775
  5. Helwig, N. E., Berry, L. N., Hadlock, T. A., Guy, S. J., & Lyford-Pike, S. (2025). Dynamic facial health predicts psychological first impressions with applications to tailored treatments for facial paralysis. Journal of Personalized Medicine, 15(11), 530. doi: 10.3390/jpm15110530
  6. Helwig, N. E. (2025). Versatile descent algorithms for group regularization and variable selection in generalized linear models. Journal of Computational and Graphical Statistics, 34(1), 239-252. doi: 10.1080/10618600.2024.2362232
  7. Duffy, K. A., & Helwig, N. E. (2024). Resting-state functional connectivity predicts attention problems in children: evidence from the ABCD Study. NeuroSci, 5(4), 445-461. doi: 10.3390/neurosci5040033
  8. Ehrmantraut, L. E., Redden, J. P., Mann, T., Helwig, N. E., & Vickers, Z. M. (2024). Self-selected diets: Exploring the factors driving food choices and satisfaction with dietary variety among independent adults. Food Quality and Preference, 105154. doi: 10.1016/j.foodqual.2024.105154
  9. Helwig, N. E. (2024). Precise tensor product smoothing via spectral splines. Stats, 7(1), 34-53. doi: 10.3390/stats7010003
  10. Helwig, N. E. (2022). Robust permutation tests for penalized splines. Stats, 5(3), 916-933. doi: 10.3390/stats5030053
  11. Helwig, N. E. (2022). Computing the real solutions of Fleishman's equations for simulating non-normal data. British Journal of Mathematical and Statistical Psychology, 75(2), 319-333. doi: 10.1111/bmsp.12259
  12. Kage, C. C., Helwig, N. E., & Ellingson, A. M. (2021). Normative cervical spine kinematics of a circumduction task. Journal of Electromyography and Kinesiology, 61, 102591. doi: 10.1016/j.jelekin.2021.102591
  13. Berry, L. N., & Helwig, N. E. (2021). Cross-validation, information theory, or maximum likelihood? A comparison of tuning methods for penalized splines. Stats, 4(3), 701-724. doi: 10.3390/stats4030042
  14. Doyle, C. M., Lasch, C., Vollman, E. P., Desjardins, C. D., Helwig, N. E., Jacob, S., Wolff, J. J., & Elison, J. T. (2021). Phenoscreening: a developmental approach to research domain criteria-motivated sampling. The Journal of Child Psychology and Psychiatry, 62(7), 884-894. doi: 10.1111/jcpp.13341
  15. Helwig, N. E. (2021). Spectrally sparse nonparametric regression via elastic net regularized smoothers. Journal of Computational and Graphical Statistics, 30(1), 182-191. doi: 10.1080/10618600.2020.1806855
  16. Kage, C. C., Akbari-Shandiz, M., Foltz, M. H., Lawrence, R. L., Brandon, T. L., Helwig, N. E., & Ellingson, A. M. (2020). Validation of an automated shape-matching algorithm for biplane radiographic spine osteokinematics and radiostereometric analysis error quantification. PLoS ONE, 15(2), e0228594. doi: 10.1371/journal.pone.0228594
  17. Almquist, Z. W., Helwig, N. E., & You, Y. (2020). Connecting Continuum of Care point-in-time homeless counts to United States Census areal units. Mathematical Population Studies, 27(1), 46-58. doi: 10.1080/08898480.2019.1636574
  18. Helwig, N. E. (2020). Multiple and generalized nonparametric regression. In P. Atkinson, S. Delamont, A. Cernat, J. W. Sakshaug, & R. A. Williams (Eds.), SAGE Research Methods Foundations. doi: 10.4135/9781526421036885885
  19. Hammell, A. E., Helwig, N. E., Kaczkurkin, A. N., Sponheim, S. R., & Lissek, S. (2020). The temporal course of over-generalized conditioned threat expectancies in posttraumatic stress disorder. Behaviour Research and Therapy, 124, 103513. doi: 10.1016/j.brat.2019.103513
  20. Helwig, N. E. (2019). Robust nonparametric tests of general linear model coefficients: A comparison of permutation methods and test statistics. NeuroImage, 201, 116030. doi: 10.1016/j.neuroimage.2019.116030
  21. Helwig, N. E., & Snodgress, M. A. (2019). Exploring individual and group differences in latent brain networks using cross-validated simultaneous component analysis. NeuroImage, 201, 116019. doi: 10.1016/j.neuroimage.2019.116019
  22. Helwig, N. E. (2019). Statistical nonparametric mapping: Multivariate permutation tests for location, correlation, and regression problems in neuroimaging. WIREs Computational Statistics, 11(2), e1457. doi: 10.1002/wics.1457
  23. Whiteford, K. L., Schloss, K. B., Helwig, N. E., & Palmer, S. E. (2018). Color, music, and emotion: Bach to the blues. i-Perception, 9(5), 1-25. doi: 10.1177/2041669518808535
  24. Lyford-Pike, S., Helwig, N. E., Sohre, N. E., Guy, S. J., & Hadlock, T. A. (2018). Predicting perceived disfigurement from facial function in patients with unilateral paralysis. Plastic and Reconstructive Surgery, 142(5), 722e-728e. doi: 10.1097/PRS.0000000000004851
  25. Liew, B. X. W., Helwig, N. E., Morris, S., & Netto, K. (2018). Influence of proximal trunk borne load on lower limb countermovement joint dynamics. Journal of Biomechanics, 79(5), 223-226. doi: 10.1016/j.jbiomech.2018.08.009
  26. Lawrence, R., Sessions, W. C., Jensen, M. C., Staker, J. L., Eid, A., Breighner, R., Helwig, N. E., Braman, J. P., & Ludewig, P. M. (2018). The effect of glenohumeral plane of elevation on supraspinatus subacromial proximity. Journal of Biomechanics, 79(5), 147-154. doi: 10.1016/j.jbiomech.2018.08.005
  27. Sohre, N. E., Adeagbo, M., Helwig, N. E., Lyford-Pike, S., & Guy, S. J. (2018). PVL: A framework for navigating the precision-variety trade-off in automated animation of smiles. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). doi: 10.1609/aaai.v32i1.11431
  28. Helwig, N. E., & Ruprecht, M. R. (2017). Age, gender, and self-esteem: a sociocultural look through a nonparametric lens. Archives of Scientific Psychology, 5(1), 19-31. doi: 10.1037/arc0000032
  29. Helwig, N. E. (2017). Regression with ordered predictors via ordinal smoothing splines. Frontiers in Applied Mathematics and Statistics, 3(15), 1-13. doi: 10.3389/fams.2017.00015
  30. Helwig, N. E. (2017). Estimating latent trends in multivariate longitudinal data via Parafac2 with functional and structural constraints. Biometrical Journal, 59(4), 783-803. doi: 10.1002/bimj.201600045
  31. Helwig, N. E., Sohre, N. E., Ruprecht, M. R., Guy, S. J., & Lyford-Pike, S. (2017). Dynamic properties of successful smiles. PLoS ONE, 12(6): e0179708. doi: 10.1371/journal.pone.0179708
  32. Helwig, N. E. (2017). Adding bias to reduce variance in psychological results: A tutorial on penalized regression. The Quantitative Methods for Psychology, 13(1), 1-19. doi: 10.20982/tqmp.13.1.p001
  33. Helwig, N. E., Shorter, K. A., Ma, P. & Hsiao-Wecksler, E. T. (2016). Smoothing spline analysis of variance models: A new tool for the analysis of cyclic biomechanical data. Journal of Biomechanics, 49(14), 3216-3222. doi: 10.1016/j.jbiomech.2016.07.035
  34. Helwig, N. E., & Ma, P. (2016). Smoothing spline ANOVA for super-large samples: Scalable computation via rounding parameters. Statistics and Its Interface, 9(4), 433-444. doi: 10.4310/SII.2016.v9.n4.a3
  35. Helwig, N. E. (2016). Efficient estimation of variance components in nonparametric mixed-effects models with large samples. Statistics and Computing, 26(6), 1319-1336. doi: 10.1007/s11222-015-9610-5
  36. Engel, S. A., Wilkins, A. J., Mand, S., Helwig, N. E., & Allen, P. M. (2016). Habitual wearers of colored lenses adapt more rapidly to the color changes the lenses produce. Vision Research, 125, 41-48. doi: 10.1016/j.visres.2016.05.003
  37. Abram, S. V., Helwig, N. E., Moodie, C. A., DeYoung, C. G., MacDonald, A. W. III, & Waller, N. G. (2016). Bootstrap enhanced penalized regression for variable selection with neuroimaging data. Frontiers in Neuroscience, 10(344), 1-15. doi: 10.3389/fnins.2016.00344
  38. Helwig, N. E., Gao, Y., Wang, S., & Ma, P. (2015). Analyzing spatiotemporal trends in social media data via smoothing spline analysis of variance. Spatial Statistics, 14(C), 491-504. doi: 10.1016/j.spasta.2015.09.002
  39. Helwig, N. E., & Ma, P. (2015). Fast and stable multiple smoothing parameter selection in smoothing spline analysis of variance models with large samples. Journal of Computational and Graphical Statistics, 24(3), 715-732. doi: 10.1080/10618600.2014.926819
  40. Helwig, N. E. (2013). The special sign indeterminacy of the direct-fitting Parafac2 model: Some implications, cautions, and recommendations for Simultaneous Component Analysis. Psychometrika, 78(4), 725-739. doi: 10.1007/S11336-013-9331-7
  41. Helwig, N. E., & Hong, S. (2013). A critique of Tensor Probabilistic Independent Component Analysis: Implications and recommendations for multi-subject fMRI data analysis. Journal of Neuroscience Methods, 213(2), 263-273. doi: 10.1016/j.jneumeth.2012.12.009
  42. Helwig, N. E., Hong, S., & Bokhari, E. (2013). Analyzing individual and group differences in multijoint multiwaveform gait data using the Parafac2 model. International Journal for Numerical Methods in Biomedical Engineering, 29(1), 62-82. doi: 10.1002/cnm.2492
  43. Helwig, N. E., Hong, S., & Polk, J. D. (2012). Parallel Factor Analysis of gait waveform data: A multimode extension of Principal Component Analysis. Human Movement Science, 31(3), 630-648. doi: 10.1016/j.humov.2011.06.011
  44. Helwig, N. E., Hong, S., Hsiao-Wecksler E. T., & Polk, J. D. (2011). Methods to temporally align gait cycle data. Journal of Biomechanics, 44(3), 561-566. doi: 10.1016/j.jbiomech.2010.09.015

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