The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Violin Plots: A Box Plot-Density Trace Synergism
Abstract
Many modifications build on Tukey's original box plot. A proposed further adaptation, the violin plot, pools the best statistical features of alternative graphical representations of batches of data. It adds the information available from local density estimates to the basic summary statistics inherent in box plots. This marriage of summary statistics and density shape into a single plot provides a useful tool for data analysis and exploration.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Popular visualizations of distributions are histograms, density plots, and violin plots (Hintze and Nelson [49] show multiple density plots side-by-side), but they seem to be hard for an uninitiated audience to grasp.”
From Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty (2021) · cites this paper as [49]
Citations
Cites
Density Estimation for Statistics and Data Analysis
Silverman, B. W. (2018) · Routledge eBooks · doi:10.1201/9781315140919 · Cited by 15,938
David, F. N., & Tukey, J. W. (1977) · Biometrics · doi:10.2307/2529486 · Cited by 12,707
Density Estimation for Statistics and Data Analysis
(1986) · Springer eBooks · doi:10.1007/978-1-4899-3324-9 · Cited by 8,514
Multivariate Density Estimation
Scott, D. W. (1992) · Wiley series in probability and statistics · doi:10.1002/9780470316849 · Cited by 3,786
Multivariate Density Estimation, Theory, Practice, and Visualbation
Ramsay, P. H. (1993) · Technometrics · doi:10.1080/00401706.1993.10485361 · Cited by 2,843
Mcgill, R., Tukey, J. W., & Larsen, W. A. (1978) · The American Statistician · doi:10.1080/00031305.1978.10479236 · Cited by 2,618
Graphical Methods for Data Analysis.
Healy, M. J. R., Chambers, J. M., Cleveland, W. S., Kleiner, B., & Tukey, P. A. (1984) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2981587 · Cited by 2,315
Graphical Methods for Data Analysis.
Fisher, N. I., Chambers, J. M., Cleveland, W. S., Kleiner, B., & Tukey, P. A. (1984) · Biometrics · doi:10.2307/2531418 · Cited by 1,982
Bulmer, M. (1978) · Sociology · doi:10.1177/003803857801200331 · Cited by 1,438
Applications, Basics and Computing of Exploratory Data Analysis.
Ross, G. J. S., Vellenian, P. F., & Hoaglin, D. C. (1983) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.2307/2347963 · Cited by 844
Research works printed but not linked: 1
- Hintze J., 1997, User's Guide, NCSS 97, Statistical System for Windows
Cited by
Sorted by citations
Items 101–200 of 1,000
Symbiosis catalyses niche expansion and diversification
Joy, J. B. (2013) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2012.2820 · Cited by 126
Gu, L., Chen, J., Yin, J., Sullivan, S. C., Wang, H., Guo, S., Zhang, L., & Kim, J. (2020) · Hydrology and earth system sciences · doi:10.5194/hess-24-451-2020 · Cited by 127
Drought hazard transferability from meteorological to hydrological propagation
Gu, L., Chen, J., Yin, J., Xu, C.-Y., & Chen, H. (2020) · Journal of Hydrology · doi:10.1016/j.jhydrol.2020.124761 · Cited by 128
Effects of sampling strategy and DNA extraction on human skin microbiome investigations
Bjerre, R. D., Hugerth, L. W., Boulund, F., Seifert, M., Johansen, J. D., & Engstrand, L. G. (2019) · Scientific Reports · doi:10.1038/s41598-019-53599-z · Cited by 132
Characterizing Population EEG Dynamics throughout Adulthood
Hashemi, A., Pino, L., Moffat, G., Mathewson, K. J., Aimone, C., Bennett, P., Schmidt, L. A., & Sekuler, A. B. (2016) · eNeuro · doi:10.1523/eneuro.0275-16.2016 · Cited by 131
A framework for assessing compound drought events from a drought propagation perspective
Wu, J., Yao, H., Chen, X., Wang, G., Bai, X., & Zhang, D. (2021) · Journal of Hydrology · doi:10.1016/j.jhydrol.2021.127228 · Cited by 128
The gut microbiome defines social group membership in honey bee colonies
Vernier, C., Chin, I. M., Adu‐Oppong, B., Krupp, J. J., Levine, J. D., Dantas, G. A., & Ben‐Shahar, Y. (2020) · Science Advances · doi:10.1126/sciadv.abd3431 · Cited by 123
Novel Computational Approach to Predict Off-Target Interactions for Small Molecules
Rao, M. S., Gupta, R., Liguori, M. J., Hu, M., Huang, X., Mantena, S. R., Mittelstadt, S. W., Blomme, E. A. G., & Vleet, T. R. V. (2019) · Frontiers in Big Data · doi:10.3389/fdata.2019.00025 · Cited by 125
Feature selection in omics prediction problems using cat scores and false non-discovery rate controlPreprint
Ahdesmaki, M. J., & Strimmer, K. (2009) · Cited by 122
Using UKCP09 probabilistic climate information for UK water resource planning
Christierson, B. V., Vidal, J., & Wade, S. D. (2011) · Journal of Hydrology · doi:10.1016/j.jhydrol.2011.12.020 · Cited by 119
Linguistic antipatterns: what they are and how developers perceive them
Arnaoudova, V., Penta, M. D., & Antoniol, G. (2015) · Empirical Software Engineering · doi:10.1007/s10664-014-9350-8 · Cited by 119
Post-mortem examination of the international financial network
Chinazzi, M., Fagiolo, G., Reyes, J. A., & Schiavo, S. (2013) · Journal of Economic Dynamics and Control · doi:10.1016/j.jedc.2013.01.010 · Cited by 130
Franchini, P., Fruciano, C., Spreitzer, M. L., Jones, J. C., Elmer, K. R., Henning, F., & Meyer, A. (2013) · Molecular Ecology · doi:10.1111/mec.12590 · Cited by 118
A framework for self-experimentation in personalized health
Karkar, R., Zia, J. K., Vilardaga, R., Mishra, S. R., Fogarty, J. A., Munson, S. A., & Kientz, J. A. (2015) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocv150 · Cited by 124
Choubin, B., & Malekian, A. (2017) · Environmental Earth Sciences · doi:10.1007/s12665-017-6870-8 · Cited by 116
Wang, Q., Li, Z., Guo, J., Zhao, C., & Cribb, M. C. (2018) · Atmospheric chemistry and physics · doi:10.5194/acp-18-12797-2018 · Cited by 116
Hu, K. (2020) · Methods and Protocols · doi:10.3390/mps3040064 · Cited by 126
Asif, D., Bibi, M., Arif, M. S., & Mukheimer, A. A. (2023) · Algorithms · doi:10.3390/a16060308 · Cited by 116
Explainable Machine Learning Algorithms For Predicting Glass Transition Temperatures
Alcobaça, E., Mastelini, S. M., Botari, T., Pimentel, B. A., Cassar, D. R., de Carvalho, A. C. P. L. F., & Zanotto, E. D. (2020) · Acta Materialia · doi:10.1016/j.actamat.2020.01.047 · Cited by 112
Expanding the Bounds of Seated Virtual Workspaces
McGill, M., Kehoe, A., Freeman, E., & Brewster, S. A. (2020) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3380959 · Cited by 115
Choosing Feature Selection and Learning Algorithms in QSAR
Eklund, M., Norinder, U., Boyer, S. K., & Carlsson, L. (2014) · Journal of Chemical Information and Modeling · doi:10.1021/ci400573c · Cited by 113
Brachi, B., Villoutreix, R., Faure, N., Hautekèete, N., Piquot, Y., Pauwels, M., Roby, D., Cuguen, J., Bergelson, J. M., & Roux, F. (2013) · Molecular Ecology · doi:10.1111/mec.12396 · Cited by 116
Flammability dynamics in the Australian Alps
Zylstra, P. (2018) · Austral Ecology · doi:10.1111/aec.12594 · Cited by 112
Hosseini, S., Turhan, B., & Mäntylä, M. (2017) · Information and Software Technology · doi:10.1016/j.infsof.2017.06.004 · Cited by 110
Brooks, G. A., & Martin, N. A. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2014.00408 · Cited by 107
Time Series Anomaly Detection for Trustworthy Services in Cloud Computing Systems
Huang, C., Min, G., Wu, Y., Ying, Y., Pei, K., & Xiang, Z. (2017) · IEEE Transactions on Big Data · doi:10.1109/tbdata.2017.2711039 · Cited by 108
Adaptive color deconvolution for histological WSI normalization
Zheng, Y., Jiang, Z., Zhang, H., Xie, F., Shi, J., & Xue, C. (2019) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2019.01.008 · Cited by 108
Ji, M., Liu, L., Du, R., & Buchroithner, M. F. (2019) · Remote Sensing · doi:10.3390/rs11101202 · Cited by 112
Savenije, M. H. F., Maspero, M., Sikkes, G. G., van Zyp, J. R. N. V. D. V., Kotte, A. N. T. J., Bol, G. H., & van den Berg, C. A. T. (2020) · Radiation Oncology · doi:10.1186/s13014-020-01528-0 · Cited by 108
The Adriatic Sea and Coast modelling suite: Evaluation of the meteotsunami forecast component
Denamiel, C., Šepić, J., Ivanković, D., & Vilibić, I. (2019) · Ocean Modelling · doi:10.1016/j.ocemod.2019.02.003 · Cited by 107
Explainable AI for Credit Assessment in Banks
de Lange, P. E., Melsom, B., Vennerød, C. B., & Westgaard, S. (2022) · Journal of risk and financial management · doi:10.3390/jrfm15120556 · Cited by 107
Feature selection in omics prediction problems using cat scores and false nondiscovery rate control
Ahdesmäki, M., & Strimmer, K. (2010) · The Annals of Applied Statistics · doi:10.1214/09-aoas277 · Cited by 107
Blood‐based metabolic signatures in Alzheimer's disease
de Leeuw, F. A., Peeters, C. F. W., Kester, M. I., Harms, A. C., Struys, E. A., Hankemeier, T., van Vlijmen, H. W. T., van der Lee, S. J., van Duijn, C. M., Scheltens, P., et al. (2017) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2017.07.006 · Cited by 104
The VoicePrivacy 2020 Challenge: Results and findings
Tomashenko, N., Wang, X., Emmanuel Vincent, A., Patino, J., Srivastava, B. M. L., Noé, .-G., Nautsch, A., Evans, N., Yamagishi, J., O’Brien, B., et al. (2022) · Computer Speech & Language · doi:10.1016/j.csl.2022.101362 · Cited by 105
Kaleda, A., Talvistu, K., Vaikma, H., Tammik, M.-L., Rosenvald, S., & Vilu, R. (2021) · Future Foods · doi:10.1016/j.fufo.2021.100092 · Cited by 109
Health-integrated heat risk assessment in Australian cities
Wang, S., Sun, Q. C., Huang, X., Tao, Y., Dong, C., Das, S., & Liu, Y. (2023) · Environmental Impact Assessment Review · doi:10.1016/j.eiar.2023.107176 · Cited by 106
Assessment of Response Bias in Mild Head Injury: Beyond Malingering Tests
Millis, S. R., & Volinsky, C. T. (2001) · Journal of Clinical and Experimental Neuropsychology · doi:10.1076/jcen.23.6.809.1017 · Cited by 103
Methods for Presenting Statistical Information: The Box Plot
Potter, K. C. (2008) · Cited by 102
The potential of novel data mining models for global solar radiation prediction
Sharafati, A., Khosravi, K., Khosravinia, P., Ahmed, K., Salman, S. A., Yaseen, Z. M., & Shahid, S. (2019) · International Journal of Environmental Science and Technology · doi:10.1007/s13762-019-02344-0 · Cited by 103
Complementary data-intelligence model for river flow simulation
Yaseen, Z. M., Awadh, S. M., Sharafati, A., & Shahid, S. (2018) · Journal of Hydrology · doi:10.1016/j.jhydrol.2018.10.020 · Cited by 101
Visual dexterity: In-hand reorientation of novel and complex object shapes
Chen, T., Tippur, M. H., Wu, S., Kumar, V., Adelson, E. H., & Agrawal, P. (2023) · Science Robotics · doi:10.1126/scirobotics.adc9244 · Cited by 101
Matzke, D., Dolan, C. V., Batchelder, W. H., & Wagenmakers, E. (2013) · Psychometrika · doi:10.1007/s11336-013-9374-9 · Cited by 108
Internal validation of STRmix™ – A multi laboratory response to PCAST
Bright, J., Richards, R., Kruijver, M., Kelly, H., McGovern, C., Magee, A., McWhorter, A., Ciecko, A., Peck, B., Baumgartner, C., et al. (2018) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2018.01.003 · Cited by 99
Adopting deep learning methods for airborne RGB fluvial scene classificationPreprint
Carbonneau, P., Dugdale, S. J., Breckon, T. P., Dietrich, J., Fonstad, M. A., Miyamoto, H., & Woodget, A. S. (2020) · doi:10.1016/j.rse.2020.112107 · Cited by 107
Choubin, B., Solaimani, K., Rezanezhad, F., Roshan, M. H., Malekian, A., & Shamshirband, S. (2019) · CATENA · doi:10.1016/j.catena.2019.104128 · Cited by 98
Cognitive model decomposition of the BART: Assessment and application
van Ravenzwaaij, D., Dutilh, G., & Wagenmakers, E. (2010) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2010.08.010 · Cited by 98
IDMVis: Temporal Event Sequence Visualization for Type 1 Diabetes Treatment Decision Support
Zhang, Y., Chanana, K., & Dunne, C. (2018) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2018.2865076 · Cited by 97
The PLS agent: Predictive modeling with PLS-SEM and agent-based simulation
Schubring, S., Lorscheid, I., Meyer, M., & Ringle, C. M. (2016) · Journal of Business Research · doi:10.1016/j.jbusres.2016.03.052 · Cited by 106
CANCERTOOL: A Visualization and Representation Interface to Exploit Cancer Datasets
Cortázar, A. R., Torrano, V., Martín-Martín, N., Caro‐Maldonado, A., Camacho, L., Heřmanová, I., Guruceaga, E., Lorenzo‐Martín, L. F., Caloto, R., Gomis, R. R., et al. (2018) · Cancer Research · doi:10.1158/0008-5472.can-18-1669 · Cited by 95
McDonald, A. D., Ferris, T. K., & Wiener, T. A. (2019) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720819856454 · Cited by 99
Clinton‐Lisell, V., & Khan, S. (2019) · AERA Open · doi:10.1177/2332858419872212 · Cited by 120
Crystal structure of the sodium–proton antiporter NhaA dimer and new mechanistic insights
Lee, C., Yashiro, S., Dotson, D., Uzdavinys, P., Iwata, S., Sansom, M. S. P., von Ballmoos, C., Beckstein, O., Drew, D., & Cameron, A. D. (2014) · The Journal of General Physiology · doi:10.1085/jgp.201411219 · Cited by 95
Schmidt, S. F., Jørgensen, M., Chen, Y., Nielsen, R., Sandelin, A., & Mandrup, S. (2011) · BMC Genomics · doi:10.1186/1471-2164-12-152 · Cited by 94
Leung, W., Shaffer, C. D., Reed, L. K., Smith, S. T., Barshop, W. D., Dirkes, W., Dothager, M., Lee, P. C., Wong, J., Xiong, D. D., et al. (2015) · G3 Genes Genomes Genetics · doi:10.1534/g3.114.015966 · Cited by 93
Zhang, W., Corwin, J., Copeland, D., Feusier, J. E., Eshbaugh, R., Chen, F., Atwell, S., & Kliebenstein, D. J. (2017) · The Plant Cell · doi:10.1105/tpc.17.00348 · Cited by 94
Enhancing road traffic flow prediction with improved deep learning using wavelet transforms
Harrou, F., Zeroual, A., Kadri, F., & Sun, Y. (2024) · Results in Engineering · doi:10.1016/j.rineng.2024.102342 · Cited by 102
Measuring Globalization of International Trade: Theory and Evidence
Arribas, I., García, F. P., & Tortosa‐Ausina, E. (2008) · World Development · doi:10.1016/j.worlddev.2008.03.009 · Cited by 93
Ianelli, J. N., Hollowed, A. B., Haynie, A. C., Mueter, F. J., & Bond, N. A. (2011) · ICES Journal of Marine Science · doi:10.1093/icesjms/fsr010 · Cited by 92
A meta-analysis of the relation between RAN and mathematics.
Koponen, T. K., Georgiou, G. K., Salmi, P., Leskinen, M., & Aro, M. T. (2017) · Journal of Educational Psychology · doi:10.1037/edu0000182 · Cited by 105
Ghimire, S., Deo, R. C., Raj, N., & Mi, J. (2019) · Energies · doi:10.3390/en12122407 · Cited by 92
Handhal, A. M., Al-Abadi, A. M., Chafeet, H. E., & Ismail, M. J. (2020) · Marine and Petroleum Geology · doi:10.1016/j.marpetgeo.2020.104347 · Cited by 93
Exploiting Hardware Performance Counters
Uhsadel, L., Georges, A., & Verbauwhede, I. M. R. (2008) · Workshop on Fault Diagnosis and Tolerance in Cryptography · doi:10.1109/fdtc.2008.19 · Cited by 92
Biologically Relevant Heterogeneity: Metrics and Practical Insights
Gough, A., Stern, A. M., Maier, J., Lezon, T. R., Shun, T., Chennubhotla, C., Schurdak, M. E., Haney, S. A., & Taylor, D. L. (2017) · SLAS DISCOVERY · doi:10.1177/2472555216682725 · Cited by 93
Nearfield Summary and Statistical Analysis of the Second AIAA Sonic Boom Prediction Workshop
Park, M. A., & Nemec, M. (2018) · Journal of Aircraft · doi:10.2514/1.c034866 · Cited by 91
Litjens, G. B. M. A., Worrell, E., & van Sark, W. G. J. H. M. (2018) · Applied Energy · doi:10.1016/j.apenergy.2018.04.018 · Cited by 91
Protein Evolution Is Faster Outside the Cell
Julenius, K. (2006) · Molecular Biology and Evolution · doi:10.1093/molbev/msl081 · Cited by 92
Extreme Reactions: Radical Right Mobilization in Eastern Europe
Bustikova, L. (2019) · doi:10.1017/9781108697248 · Cited by 90
Trumbull, R. B., Codeço, M. S., Jiang, S., Palmer, M. R., & Slack, J. F. (2020) · Ore Geology Reviews · doi:10.1016/j.oregeorev.2020.103682 · Cited by 89
Thomas, E. M., Lin, H., Duffy, C. J., Sullivan, P., Holmes, G. H., Brantley, S. L., & Jin, L. (2013) · Vadose Zone Journal · doi:10.2136/vzj2013.01.0029 · Cited by 89
Mahecha, M. D., Reichstein, M., Jung, M., Seneviratne, S. I., Zaehle, S., de Beer, C., Braakhekke, M. C., Carvalhais, N., Lange, H., Maire, G. L., et al. (2010) · Journal of Geophysical Research Atmospheres · doi:10.1029/2009jg001016 · Cited by 89
Bornmann, L. (2013) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.22792 · Cited by 87
Katz, B. P., Kudela, M., Harezlak, J., McCrea, M., McAllister, T. W., & Broglio, S. P. (2018) · Sports Medicine · doi:10.1007/s40279-018-0875-7 · Cited by 87
Near, T. J., MacGuigan, D. J., Parker, E., Struthers, C. D., JONES, C. D., & Dornburg, A. (2018) · Molecular Phylogenetics and Evolution · doi:10.1016/j.ympev.2018.09.001 · Cited by 84
Goodness of fit for stochastic actor-oriented models
Lospinoso, J. A., & Snijders, T. A. B. (2019) · Methodological Innovations · doi:10.1177/2059799119884282 · Cited by 87
Just-In-Time Defect Identification and Localization: A Two-Phase Framework
Yan, M. L., Xia, X., Fan, Y., Hassan, A. E., Lo, D., & Li, S. (2020) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2020.2978819 · Cited by 91
Assessing the Refactorability of Software Clones
Tsantalis, N., Mazinanian, D., & Krishnan, G. P. (2015) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2015.2448531 · Cited by 87
Moran, J. L., & Solomon, P. J. (2012) · BMC Medical Research Methodology · doi:10.1186/1471-2288-12-68 · Cited by 86
Marchessaux, G., Mangano, M. C., Bizzarri, S., M’Rabet, C., Principato, E., Lago, N., Veyssiere, D., Garrido, M., Scyphers, S. B., & Sarà, G. (2022) · Marine Policy · doi:10.1016/j.marpol.2022.105461 · Cited by 86
Accuracy of performance counter measurements
Zaparanuks, D., Jovic, M., & Hauswirth, M. (2009) · IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) · doi:10.1109/ispass.2009.4919635 · Cited by 86
Latent Curve Models and Latent Change Score Models Estimated in R
Ghisletta, P., & McArdle, J. J. (2012) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705511.2012.713275 · Cited by 87
Calibrating Ground-Based Radars against TRMM and GPM
Warren, R. A., Protat, A., Siems, S. T., Ramsay, H. A., Louf, V., Manton, M. J., & Kane, T. A. (2017) · Journal of Atmospheric and Oceanic Technology · doi:10.1175/jtech-d-17-0128.1 · Cited by 84
Boone, K., Wisdom, C., Camarda, K. V., Spencer, P., & Tamerler, C. (2021) · BMC Bioinformatics · doi:10.1186/s12859-021-04156-x · Cited by 89
Biswas, S., Logan, N. S., Davies, L. N., Sheppard, A. L., & Wolffsohn, J. S. (2023) · Ophthalmic and Physiological Optics · doi:10.1111/opo.13207 · Cited by 84
ViewBS: a powerful toolkit for visualization of high-throughput bisulfite sequencing data
Huang, X., Zhang, S., Li, K., Thimmapuram, J., & Xie, S. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx633 · Cited by 83
A default Bayesian hypothesis test for mediation
Nuijten, M. B., Wetzels, R., Matzke, D., Dolan, C. V., & Wagenmakers, E. (2014) · Behavior Research Methods · doi:10.3758/s13428-014-0470-2 · Cited by 85
Selecting the optimal artificial reefs to achieve fish habitat enhancement goals
Lemoine, H. R., Paxton, A. B., Anisfeld, S. C., Rosemond, R. C., & Peterson, C. H. (2019) · Biological Conservation · doi:10.1016/j.biocon.2019.108200 · Cited by 82
Displaying Uncertainty With Shading
Jackson, C. H. (2008) · The American Statistician · doi:10.1198/000313008x370843 · Cited by 82
Olsen, E., Kaplan, I. C., Ainsworth, C. H., Fay, G., Gaichas, S., Gamble, R. J., Girardin, R., Eide, C. H. S., Ihde, T. F., Morzaria‐Luna, H. N., et al. (2018) · Frontiers in Marine Science · doi:10.3389/fmars.2018.00064 · Cited by 81
Genetic-Algorithm-Optimized Sequential Model for Water Temperature Prediction
Stajkowski, S., Kumar, D., Samui, P., Bonakdari, H., & Gharabaghi, B. (2020) · Sustainability · doi:10.3390/su12135374 · Cited by 82
Time-series weather prediction in the Red sea using ensemble transformers
Hittawe, M. M., Harrou, F., Togou, M. A., Sun, Y., & Knio, O. (2024) · Applied Soft Computing · doi:10.1016/j.asoc.2024.111926 · Cited by 83
Manolache, S., Niță, A., Ciocănea, C. M., Popescu, V. D., & Rozyłowicz, L. (2018) · Journal of Environmental Management · doi:10.1016/j.jenvman.2018.01.076 · Cited by 82
Health-related quality of life of people with HIV
Engelhard, E. A. N., Smit, C., van Dijk, P. R., Kuijper, T. M., Wermeling, P. R., Weel, A. E. A. M., de Boer, M. R., Brinkman, K., Geerlings, S. E., & Nieuwkerk, P. T. (2017) · AIDS · doi:10.1097/qad.0000000000001672 · Cited by 79
Baccarini, A., Dommen, J., Lehtipalo, K., Henning, S., Modini, R. L., Beer, M. G., Baltensperger, U., & Schmale, J. (2021) · Journal of Geophysical Research Atmospheres · doi:10.1029/2021jd035126 · Cited by 79
Alizamir, M., Wang, M., Ikram, R. M. A., Gholampour, A., Ahmed, K. O., Heddam, S., & Kim, S. (2025) · Results in Engineering · doi:10.1016/j.rineng.2025.104307 · Cited by 87
Understanding public response to a congestion charge: A random-effects ordered logit approach
Zheng, Z., Liu, Z., Liu, C., & Shiwakoti, N. (2014) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2014.10.016 · Cited by 79
Acoustic localization of antbirds in a Mexican rainforest using a wireless sensor network
Collier, T. C., Kirschel, A. N. G., & TAYLOR, C. E. (2010) · The Journal of the Acoustical Society of America · doi:10.1121/1.3425729 · Cited by 79
Zlinszky, A., Schroiff, A., Kania, A., Déak, B., Mücke, W., Vári, Á., Székely, B., & Pfeifer, N. (2014) · Remote Sensing · doi:10.3390/rs6098056 · Cited by 79
Assessment of forecasting methods on performance of photovoltaic-battery systems
Litjens, G. B. M. A., Worrell, E., & van Sark, W. G. J. H. M. (2018) · Applied Energy · doi:10.1016/j.apenergy.2018.03.154 · Cited by 79
Histone macroH2A1.2 promotes metabolic health and leanness by inhibiting adipogenesis
Pazienza, V., Panebianco, C., Rappa, F., Memoli, D., Borghesan, M., Cannito, S., Oji, A., Mazza, G., Tamburrino, D., Fusai, G., et al. (2016) · Epigenetics & Chromatin · doi:10.1186/s13072-016-0098-9 · Cited by 78
Wang, Q., & Li, S. (2020) · Sustainable Cities and Society · doi:10.1016/j.scs.2020.102629 · Cited by 83
Metadata
- Authors
- Hintze, J. L., & Nelson, R. D.
- Affiliations
- Brigham Young University (US)
- Venue
- The American Statistician
- Publisher
- Informa UK Limited
- Published
- 1998-05
- Volume
- 52
- Issue
- 2
- Pages
- 181-184
- ISSN
- 0003-1305 (ISSN-L)
- 1537-2731
- OpenAlex
- W2042204882
- Cited by
- 1,802
- References
- 17
- Citations by year
- 2026: 97 · 2025: 138 · 2024: 181 · 2023: 170 · 2022: 159 · 2021: 184 · 2020: 151 · 2019: 124 · 2018: 112 · 2017: 83 · 2016: 74 · 2015: 60 · 2014: 69 · 2013: 57 · 2012: 40
- FWCI
- 2.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The American Statistician (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Data Visualization and Analytics
- Physical Sciences › Computer Science › Software › SAS software applications and methods
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Keywords
- violin plots, box plots, density estimation, data visualization, summary statistics, exploratory data analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review