Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median

False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant

Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011) · Psychological Science · doi:10.1177/0956797611417632 · Cited by 6,567

The Influence Curve and Its Role in Robust Estimation

Hampel, F. R. (1974) · Journal of the American Statistical Association · doi:10.1080/01621459.1974.10482962 · Cited by 2,847

Alternatives to the Median Absolute Deviation

Rousseeuw, P. J., & Croux, C. (1993) · Journal of the American Statistical Association · doi:10.1080/01621459.1993.10476408 · Cited by 2,672

Methods for dealing with reaction time outliers.

Ratcliff, R. (1993) · Psychological Bulletin · doi:10.1037/0033-2909.114.3.510 · Cited by 2,142

Alternatives to the Median Absolute Deviation

Rousseeuw, P. J., & Croux, C. (1993) · Journal of the American Statistical Association · doi:10.2307/2291267 · Cited by 1,489

Outliers detection and treatment: a review.

Cousineau, D., & Chartier, S. (2010) · International journal of psychological research · doi:10.21500/20112084.844 · Cited by 719

Handbook of Research Methods. in Social and Personality Psychology

Lai, H. L. T. (2000) · Cited by 629

Short Report: Reaction Time Analysis with Outlier Exclusion: Bias Varies with Sample Size

Miller, J. O. (1991) · The Quarterly Journal of Experimental Psychology Section A · doi:10.1080/14640749108400962 · Cited by 408

OUTLIER DETECTION AND TREATMENT IN I/O PSYCHOLOGY: A SURVEY OF RESEARCHER BELIEFS AND AN EMPIRICAL ILLUSTRATION

ORR, J. M., Sackett, P. R., & DuBois, C. L. Z. (1991) · Personnel Psychology · doi:10.1111/j.1744-6570.1991.tb02401.x · Cited by 183

Human neuronal excitation/inhibition balance explains and predicts neurostimulation induced learning benefits

van Bueren, N. E. R., van der Ven, S. H. G., Hochman, S., Sella, F., & Kadosh, R. C. (2023) · PLoS Biology · doi:10.1371/journal.pbio.3002193 · Cited by 49

Evaluation of PM2.5 spatio-temporal variability and hotspot formation using low-cost sensors across urban-rural landscape in lucknow, India

Madhwal, S., Tripathi, S. N., Bergin, M., Bhave, P. V., de Foy, B., Reddy, T. V. R., Chaudhry, S. K., Jain, V., Garg, N., & Lalwani, P. (2023) · Atmospheric Environment · doi:10.1016/j.atmosenv.2023.120302 · Cited by 38

Towards data and analytics driven B2B-banking for green finance: A cross-selling use case study

Chang, V. I. C., Hahm, N., Xu, Q. A., Vijayakumar, P., & Liu, L. (2024) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2024.123542 · Cited by 47

Characterizing implicit mental health associations across clinical domains

Werntz, A. J., Steinman, S. A., Glenn, J. J., Nock, M. K., & Teachman, B. A. (2016) · Journal of Behavior Therapy and Experimental Psychiatry · doi:10.1016/j.jbtep.2016.02.004 · Cited by 38

Google Flu Trends Spatial Variability Validated Against Emergency Department Influenza-Related Visits

Klembczyk, J. J., Jalalpour, M., Levin, S., Washington, R., Pines, J. M., Rothman, R. E., & Dugas, A. F. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5585 · Cited by 38

The Parkinsonian Subthalamic Network: Measures of Power, Linear, and Non-linear Synchronization and their Relationship to L-DOPA Treatment and OFF State Motor Severity

West, T. O., Farmer, S. F., Luc Berthouze, A., Jha, A., Beudel, M., Foltynie, T., Limousin, P. D., Zrinzo, L. U., Brown, P., & Vladimir Litvak, A. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00517 · Cited by 34

Understanding Playlist Creation on Music Streaming Platforms

Pichl, M., Zangerle, E., & Specht, G. (2016) · IEEE International Symposium on Multimedia (ISM) · doi:10.1109/ism.2016.0107 · Cited by 38

Evaluating Risk to People and Property for Aircraft Emergency Landing Planning

Donato, P. F. A. D., & Atkins, E. M. (2017) · Journal of Aerospace Information Systems · doi:10.2514/1.i010513 · Cited by 38

Designing Precise and Robust Dialogue Response Evaluators

Zhao, T., Lala, D., & Kawahara, T. (2020) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2020.acl-main.4 · Cited by 41

Near-duplicate detection in web app model inference

Yandrapally, R., Stocco, A., & Mesbah, A. (2020) · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) · doi:10.1145/3377811.3380416 · Cited by 38

The relationship between value-based actions, psychological distress and well-being: A multilevel diary study

Grégoire, S., Doucerain, M., Morin, L., & Finkelstein-Fox, L. (2021) · Journal of Contextual Behavioral Science · doi:10.1016/j.jcbs.2021.03.006 · Cited by 38

Robotic Locomotor Training Leads to Cardiovascular Changes in Individuals With Incomplete Spinal Cord Injury Over a 24-Week Rehabilitation Period: A Randomized Controlled Pilot Study

Evans, R. W., Shackleton, C. L., West, S. J., Derman, W. E., Rauch, L., Baalbergen, E., & Albertus, Y. (2021) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2021.03.018 · Cited by 41

The Interplay Between Quality of Life and Resilience Factors in Later Life: A Network Analysis

Brinkhof, L. P., Huth, K. B. S., Murre, J. M. J., de Wit, S., Krugers, H. J., & Ridderinkhof, K. R. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.752564 · Cited by 45

Enabling Continuous Wearable Reflectance Pulse Oximetry at the Sternum

Chan, M., Ganti, V. G., Heller, J. A., Abdallah, C. A., Etemadi, M., & Inan, O. T. (2021) · Biosensors · doi:10.3390/bios11120521 · Cited by 38

That's not natural! Consumer response to disconfirmed expectations about ‘natural’ food

Schirmacher, H., Elshiewy, O., & Boztuğ, Y. (2022) · Appetite · doi:10.1016/j.appet.2022.106270 · Cited by 40

Isoform-specific hyperactivation of calpain-2 occurs presymptomatically at the synapse in Alzheimer’s disease mice and correlates with memory deficits in human subjects

Ahmad, F., Das, D., Kommaddi, R. P., Diwakar, L., Gowaikar, R., Rupanagudi, K. V., Bennett, D. A., & Ravindranath, V. (2018) · Scientific Reports · doi:10.1038/s41598-018-31073-6 · Cited by 40

The Impact of Business Support Services for Small and Medium Enterprises on Firm Performance in Low- and Middle-Income Countries: A Systematic Review

Piza, C., Cravo, T. A., Taylor, L., Gonzalez, L., Musse, I., Furtado, I., Sierra, A. C., & Abdelnour, S. (2016) · Campbell Systematic Reviews: Better Evidence for a Better World · doi:10.4073/csr.2016.1 · Cited by 58

A 2-yr Randomized Controlled Trial on Creatine Supplementation during Exercise for Postmenopausal Bone Health

Chilibeck, P. D., Candow, D. G., Gordon, J. J., DUFF, W. R. D., Mason, R., Shaw, K. A., Taylor‐Gjevre, R. M., Nair, B., & Zello, G. A. (2023) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0000000000003202 · Cited by 52

Global natural concentrations of Rare Earth Elements in aquatic organisms: Progress and lessons from fifty years of studies.

Pereto, C., Baudrimont, M., & Coynel, A. (2024) · Science of the Total Environment · doi:10.1016/j.scitotenv.2024.171241 · Cited by 38

Tools for monitoring system suitability in LC MS/MS centric proteomic experiments

Bereman, M. S. (2014) · PROTEOMICS · doi:10.1002/pmic.201400373 · Cited by 36

From Power to Inaction

Durso, G. R. O., Briñol, P., & Petty, R. E. (2016) · Psychological Science · doi:10.1177/0956797616669947 · Cited by 37

Nitrous oxide emissions from sugarcane fields in the Brazilian Cerrado

da Silva, J. F., de Carvalho, A. M., Rein, T. A., Coser, T. R., Ribeiro, W. Q., Vieira, D. L., & Coomes, D. A. (2017) · Agriculture Ecosystems & Environment · doi:10.1016/j.agee.2017.05.019 · Cited by 37

Guilt Dynamics: Consequences of Temporally Separating Decisions and Actions

Duke, K. E., & Amir, O. (2018) · Journal of Consumer Research · doi:10.1093/jcr/ucy049 · Cited by 37

Vertical Redistribution of Soil Organic Carbon Pools After Twenty Years of Nitrogen Addition in Two Temperate Coniferous Forests

Forstner, S. J., Wechselberger, V., Müller, S., Keiblinger, K. M., Díaz‐Pinés, E., Wanek, W., Schleppi, P., Hagedorn, F., Gundersen, P., Tatzber, M., et al. (2018) · Ecosystems · doi:10.1007/s10021-018-0275-8 · Cited by 37

Real-time feature selection technique with concept drift detection using adaptive micro-clusters for data stream mining

Hammoodi, M. S., Stahl, F. T., & Badii, A. (2018) · Knowledge-Based Systems · doi:10.1016/j.knosys.2018.08.007 · Cited by 37

Assessing variability in carbon footprint throughout the food supply chain: a case study of Valencian oranges

Ribal, J., Estruch, V., Clemente, G., Fenollosa, M. L., & Sanjuán, N. (2019) · The International Journal of Life Cycle Assessment · doi:10.1007/s11367-018-01580-9 · Cited by 37

Tree performance in a biodiversity enrichment experiment in an oil palm landscape

Zemp, D. C., Gérard, A., Hölscher, D., Ammer, C., Irawan, B., Sundawati, L., Teuscher, M., & Kreft, H. (2019) · Journal of Applied Ecology · doi:10.1111/1365-2664.13460 · Cited by 42

Data Independent Acquisition Proteomic Analysis Can Discriminate between Actinic Keratosis, Bowen’s Disease, and Cutaneous Squamous Cell Carcinoma

Azimi, A., Yang, P., Ali, M., Howard, V., Mann, G. J., Alexander, K. L., & Fernández, P. (2019) · Journal of Investigative Dermatology · doi:10.1016/j.jid.2019.06.128 · Cited by 38

The role of the fornix in human navigational learning

Hodgetts, C. J., Stefani, M., Williams, A. N., Kolarik, B. S., Yonelinas, A. P., Ekstrom, A. D., Lawrence, A. D., Zhang, J., & Graham, K. S. (2019) · Cortex · doi:10.1016/j.cortex.2019.10.017 · Cited by 36

Testing the Effectiveness of a Disclosure in Activating Children’s Advertising Literacy in the Context of Embedded Advertising in Vlogs

Hoek, R. W., Rozendaal, E., van Schie, H. T., van Reijmersdal, E. A., & Buijzen, M. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.00451 · Cited by 37

Task specificity impacts dual-task interference in older adults

Fallahtafti, F., Boron, J. B., Venema, D. M., Kim, H. J., & Yentes, J. M. (2020) · Aging Clinical and Experimental Research · doi:10.1007/s40520-020-01575-3 · Cited by 37

A Review of Approaches for the Detection and Treatment of Outliers in Processing Wind Turbine and Wind Farm Measurements

Zou, M., & Djokic, S. (2020) · Energies · doi:10.3390/en13164228 · Cited by 37

Longitudinal Reproducibility of Neurite Orientation Dispersion and Density Imaging (NODDI) Derived Metrics in the White Matter

Lehmann, N., Aye, N., Kaufmann, J., Heinze, H., Düzel, E., Ziegler, G., & Taubert, M. (2021) · Neuroscience · doi:10.1016/j.neuroscience.2021.01.005 · Cited by 36

Evapotranspiration partitioning and its interannual variability over a winter wheat-summer maize rotation system in the North China Plain

Hu, X., & Lei, H. (2021) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2021.108635 · Cited by 37

Contemporary gene flow between wild An. gambiae s.s. and An. arabiensis

Weetman, D., Steen, K., Rippon, E. J., Mawejje, H. D., Donnelly, M. J., & Wilding, C. S. (2014) · Parasites & Vectors · doi:10.1186/1756-3305-7-345 · Cited by 35

The role of time on task in computer-based low-stakes assessment of cross-curricular skills.

Kupiainen, S., Vainikainen, M., Marjanen, J., & Hautamäki, J. (2014) · Journal of Educational Psychology · doi:10.1037/a0035507 · Cited by 37

Probabilistic-based assessment of a masonry arch bridge considering inferential procedures

Moreira, V. N., Matos, J. C., & Oliveira, D. V. (2016) · Engineering Structures · doi:10.1016/j.engstruct.2016.11.067 · Cited by 37

Reading Poetry and Prose: Eye Movements and Acoustic Evidence

Blohm, S., Versace, S., Methner, S., Wagner, V., Schlesewsky, M., & Menninghaus, W. (2022) · Discourse Processes · doi:10.1080/0163853x.2021.2015188 · Cited by 36

Deformation prediction of large-scale civil structures using spatiotemporal clustering and empirical mode decomposition-based long short-term memory network

Shan, J., Zhang, X., Liu, Y., Zhang, C., & Zhou, J. (2023) · Automation in Construction · doi:10.1016/j.autcon.2023.105222 · Cited by 37

Image Region Duplication Forgery Detection Based on Angular Radial Partitioning and Harris Key-Points

Uliyan, D. M., Jalab, H. A., Wahab, A. W. A., & Sadeghi, S. (2016) · Symmetry · doi:10.3390/sym8070062 · Cited by 36

Cubozoan Sting-Site Seawater Rinse, Scraping, and Ice Can Increase Venom Load: Upending Current First Aid Recommendations

Yanagihara, A. A., & Wilcox, C. L. (2017) · Toxins · doi:10.3390/toxins9030105 · Cited by 36

Novel phosphonate analogs of sulforaphane: Synthesis, in vitro and in vivo anticancer activity

Psurski, M., Janczewski, Ł., Świtalska, M., Gajda, A., Goszczyński, T. M., Oleksyszyn, J., Wietrzyk, J., & Gajda, T. (2017) · European Journal of Medicinal Chemistry · doi:10.1016/j.ejmech.2017.03.028 · Cited by 36

Taking PISA Seriously: How Accurate are Low-Stakes Exams?

Akyol, P., Krishna, K., & Wang, J. (2021) · Journal of Labor Research · doi:10.1007/s12122-021-09317-8 · Cited by 36

An Investigation of Compensation and Adaptation to Auditory Perturbations in Individuals With Acquired Apraxia of Speech

Ballard, K. J., Halaki, M., Sowman, P. F., Kha, A., Daliri, A., Robin, D. A., Tourville, J. A., & Guenther, F. H. (2018) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2018.00510 · Cited by 38

A Statistical Approach to Estimate Imbalance-Induced Energy Losses for Data-Scarce Low Voltage Networks

Fang, L.-R., Ma, K., Li, R., Wang, Z., & Shi, H. (2019) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2019.2891963 · Cited by 29

Active acoustic damage detection of structural cavities using internal acoustic excitations

Beale, C., İnalpolat, M., & Niezrecki, C. (2019) · Structural Health Monitoring · doi:10.1177/1475921719835761 · Cited by 36

A Structural Equation Model of Perceived Autonomy Support and Growth Mindset in Undergraduate Students: The Mediating Role of Sense of Coherence

Ma, C., Ma, Y., & Lan, X. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.02055 · Cited by 39

Genetic differences and longevity‐related phenotypes influence lifespan and lifespan variation in a sex‐specific manner in mice

Yuan, R., Musters, C. J. M., Zhu, Y. X., Evans, T. R., Sun, Y., Chesler, E. J., Peters, L. L., Harrison, D. E., & Bartke, A. (2020) · Aging Cell · doi:10.1111/acel.13263 · Cited by 36

Morphometric Analysis of Retinal Pigment Epithelial Cells From C57BL/6J Mice During Aging

Kim, Y.-K., Yu, H., Summers, V. R., Donaldson, K. J., Ferdous, S., Shelton, D. A., Zhang, N., Chrenek, M. A., Jiang, Y., Grossniklaus, H. E., et al. (2021) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.62.2.32 · Cited by 36

Human mobility in a Bronze Age Vatya ‘urnfield’ and the life history of a high-status woman

Cavazzuti, C., Hajdu, T., Lugli, F., Sperduti, A., Vicze, M., Horváth, A., Major, I., Molnár, M., Palcsu, L., & Kiss, V. (2021) · PLoS ONE · doi:10.1371/journal.pone.0254360 · Cited by 41

Outlier Detection in Buildings’ Power Consumption Data Using Forecast Error

Nascimento, G. F. M., Würtz, F., Kuo‐Peng, P., DELINCHANT, B., & Batistela, N. J. (2021) · Energies · doi:10.3390/en14248325 · Cited by 36

LASense

Li, D., Liu, J., Lee, S. I., & Xiong, J. (2022) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3517253 · Cited by 36

Development and validation of an fMRI-informed EEG model of reward-related ventral striatum activation

Singer, N., Poker, G., Dunsky, N., Nemni, S., Balter, S. R., Doron, M., Baker, T. E., Dagher, A., Zatorre, R. J., & Hendler, T. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120183 · Cited by 35

The Effect of Expected Value on Attraction Effect Preference Reversals

Farmer, G., Warren, P. A., El‐Deredy, W., & Howes, A. (2016) · Journal of Behavioral Decision Making · doi:10.1002/bdm.2001 · Cited by 36

What is attention bias variability? Examining the potential roles of attention control and response time variability in its relationship with anxiety

Clarke, P. J. F., Marinovic, W., Todd, J., Basanovic, J., Chen, N. T. M., & Notebaert, L. (2020) · Behaviour Research and Therapy · doi:10.1016/j.brat.2020.103751 · Cited by 38

Anxiety and Depression in Gifted Individuals: A Systematic and Meta-Analytic Review

Duplenne, L., Bourdin, B., Fernandez, D., Blondelle, G., & Aubry, A. (2023) · Gifted Child Quarterly · doi:10.1177/00169862231208922 · Cited by 51

Exploring physics students’ engagement with online instructional videos in an introductory mechanics course

Lin, S.-Y., Aiken, J. M., Seaton, D. T., Douglas, S. S., Greco, E. F., Thoms, B. D., & Schatz, M. F. (2017) · Physical Review Physics Education Research · doi:10.1103/physrevphyseducres.13.020138 · Cited by 35

Cautionary note on the use of genetic programming in statistical downscaling

Sachindra, D. A., Ahmed, K., Shahid, S., & Perera, B. J. C. (2018) · International Journal of Climatology · doi:10.1002/joc.5508 · Cited by 35

High Throughput Screening Technologies in Biomass Characterization

Decker, S. R., Harman-Ware, A. E., Happs, R. M., Wolfrum, E. J., Tuskan, G. A., Kainer, D., Oguntimein, G. B., Rodríguez, M., Weighill, D. A., Jones, P. C., et al. (2018) · Frontiers in Energy Research · doi:10.3389/fenrg.2018.00120 · Cited by 35

One robot doesn’t fit all: aligning social robot appearance and job suitability from a Middle Eastern perspective

Złotowski, J. A., Khalil, A., & Abdallah, S. (2019) · AI & Society · doi:10.1007/s00146-019-00895-x · Cited by 35

Multivariate Regression-Based Convolutional Neural Network Model for Fundus Image Quality Assessment

Raj, A., Shah, N. A., Tiwari, A. K., & Martini, M. G. (2020) · IEEE Access · doi:10.1109/access.2020.2982588 · Cited by 34

[11C]PIB amyloid quantification: effect of reference region selection

Heeman, F., Hendriks, J., Alves, I. L., Ossenkoppele, R., Tolboom, N., van Berckel, B. N. M., Lammertsma, A. A., & Yaqub, M. M. (2020) · EJNMMI Research · doi:10.1186/s13550-020-00714-1 · Cited by 39

A machine learning based modelling framework to predict nitrate leaching from agricultural soils across the Netherlands

Spijker, J., Fraters, B., & Vrijhoef, A. (2021) · Environmental Research Communications · doi:10.1088/2515-7620/abf15f · Cited by 35

An efficient clustering with robust outlier mitigation for Wi-Fi fingerprint based indoor positioning

Sadhukhan, P., Gain, S., Dahal, K. P., Chattopadhyay, S., Garain, N., & Wang, X. (2021) · Applied Soft Computing · doi:10.1016/j.asoc.2021.107549 · Cited by 35

Digital monitoring of grain conditions in large-scale bulk storage facilities based on spatiotemporal distributions of grain temperature

Wu, W., Cui, H., Han, F., Liu, Z., Xiao-ming, W., Wu, Z., & Zhang, Q. (2021) · Biosystems Engineering · doi:10.1016/j.biosystemseng.2021.08.028 · Cited by 35

Dimethylammonium Addition to Halide Perovskite Precursor Increases Vertical and Lateral Heterogeneity

Jariwala, S., Kumar, R. E., Eperon, G. E., Shi, Y., Fenning, D. P., & Ginger, D. S. (2021) · ACS Energy Letters · doi:10.1021/acsenergylett.1c02302 · Cited by 35

A new age model and chemostratigraphic framework for the Maastrichtian type area (southeastern Netherlands, northeastern Belgium)

Vellekoop, J., Kaskes, P., Sinnesael, M., Huygh, J. J. C., Déhais, T., Jagt, J. W. M., Speijer, R. P., & Claeys, P. (2022) · Newsletters on Stratigraphy · doi:10.1127/nos/2022/0703 · Cited by 35

Holistic characterization of flash flood vulnerability: Construction and validation of an integrated multidimensional vulnerability index

Aroca‐Jiménez, E., Bodoque, J. M., García, J. A., & Figueroa-García, J. E. (2022) · Journal of Hydrology · doi:10.1016/j.jhydrol.2022.128083 · Cited by 35

Unobtrusive Estimation of Cardiovascular Parameters with Limb Ballistocardiography

Yao, Y., Shin, S., Mousavi, A. S., Kim, C., Xu, L., Mukkamala, R., & Hahn, J. (2019) · Sensors · doi:10.3390/s19132922 · Cited by 35

The t test and beyond: Recommendations for testing the central tendencies of two independent samples in research on speech, language and hearing pathology

Rietveld, T. C. M., & van Hout, R. W. N. M. (2015) · Journal of Communication Disorders · doi:10.1016/j.jcomdis.2015.08.002 · Cited by 35

Mirroring multiple agents: Motor resonance during action observation is modulated by the number of agents

Cracco, E., De Coster, L., Andres, M., & Brass, M. (2016) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsw059 · Cited by 38

Supporting and expressing support for environmental policies

Kaiser, F. G., Gerdes, R., & König, F. (2023) · Journal of Environmental Psychology · doi:10.1016/j.jenvp.2023.101997 · Cited by 37

Beta and theta oscillations track effort and previous reward in the human basal ganglia and prefrontal cortex during decision making

Hoy, C. W., de Hemptinne, C., Wang, S. S., Harmer, C. J., Apps, M. A. J., Husain, M., Starr, P. A., & Little, S. J. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2322869121 · Cited by 34

Robust anomaly detection algorithms for real-time big data: Comparison of algorithms

Hasani, Z. (2017) · Mediterranean Conference on Embedded Computing (MECO) · doi:10.1109/meco.2017.7977130 · Cited by 36

Caffeine enhances activity thermogenesis and energy expenditure in rats

Clark, K. S., Coleman, C., Shelton, R., Heemstra, L. A., & Novak, C. M. (2019) · Clinical and Experimental Pharmacology and Physiology · doi:10.1111/1440-1681.13065 · Cited by 34

Predicting first test day milk yield of dairy heifers

Dallago, G. M., de Figueiredo, D. M., Andrade, P. C. D. R., dos Santos, R. A., Lacroix, R., Santschi, D. E., & Lefebvre, D. M. (2019) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2019.105032 · Cited by 33

Validation of SAGE III/ISS Solar Water Vapor Data With Correlative Satellite and Balloon‐Borne Measurements

Davis, S., Damadeo, R., Flittner, D. E., Rosenlof, K. H., Park, M., Randel, W. J., Hall, E. G., Huber, D., Hurst, D. F., Jordan, A. F., et al. (2020) · Journal of Geophysical Research Atmospheres · doi:10.1029/2020jd033803 · Cited by 34

Soil quality index for assessing phosphate mining restoration in a hyper-arid environment

Levi, N., Hillel, N., Zaady, E., Rotem, G., Ziv, Y., Karnieli, A., & Paz‐Kagan, T. (2021) · Ecological Indicators · doi:10.1016/j.ecolind.2021.107571 · Cited by 35

Association of Generic Competition With Price Decreases in Physician-Administered Drugs and Estimated Price Decreases for Biosimilar Competition

Dickson, S., & Kent, T. (2021) · JAMA Network Open · doi:10.1001/jamanetworkopen.2021.33451 · Cited by 34

Spatiotemporal Evolution of Wetland Eco-Hydrological Connectivity in the Poyang Lake Area Based on Long Time-Series Remote Sensing Images

Xia, Y., Fang, C., Lin, H., Li, H., & Wu, B. (2021) · Remote Sensing · doi:10.3390/rs13234812 · Cited by 34

Government pandemic response strategies for AEC enterprises: lessons from COVID-19

Zamani, S. H., Rahman, R. A., Fauzi, M. A., & Yusof, L. M. (2022) · Journal of Engineering Design and Technology · doi:10.1108/jedt-10-2021-0540 · Cited by 34

Threshold center-symmetric local binary convolutional neural networks for bilingual handwritten digit recognition

Al-wajih, E., & Ghazali, R. (2022) · Knowledge-Based Systems · doi:10.1016/j.knosys.2022.110079 · Cited by 36

Routliers: Robust Outliers Detection

Delacre, M., & Klein, O. (2019) · doi:10.32614/cran.package.routliers · Cited by 34

Decomposition Methods for Machine Learning with Small, Incomplete or Noisy Datasets

Caiafa, C. F., Solé-Casals, J., Marti-Puig, P., Zhe, S., & Tanaka, T. (2020) · Applied Sciences · doi:10.3390/app10238481 · Cited by 33

Muscle-Specific High-Density Electromyography Arrays for Hand Gesture Classification

Lara, J. E., Cheng, L. K., Rohrle, O., & Paskaranandavadivel, N. (2021) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2021.3131297 · Cited by 33

Bifactor exploratory structural equation modeling: A meta-analytic review of model fit

Gegenfurtner, A. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.1037111 · Cited by 43

Measurement Accuracy of the HTC VIVE Tracker 3.0 Compared to Vicon System for Generating Valid Positional Feedback in Virtual Reality

Merker, S., Pastel, S., Bürger, D., Schwadtke, A., & Witte, K. (2023) · Sensors · doi:10.3390/s23177371 · Cited by 33

Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction

Baran, K., & Kloskowski, A. (2023) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.3c05521 · Cited by 33

Urban form and seasonal PM2.5 dynamics: Enhancing air quality prediction using interpretable machine learning and IoT sensor data

Lee, J., Barquilla, C. A. M., Park, K., & Hong, A. (2024) · Sustainable Cities and Society · doi:10.1016/j.scs.2024.105976 · Cited by 33

Self-Management for Primary School Students Demonstrating Problem Behavior in Regular Classrooms: Evidence Review of Single-Case Design Research

Busacca, M. L., Anderson, A., & Moore, D. W. (2015) · Journal of Behavioral Education · doi:10.1007/s10864-015-9230-3 · Cited by 33

A cluster-based approach to selecting representative stimuli from the International Affective Picture System (IAPS) database

Constantinescu, A. C., Wolters, M. K., Moore, A., & MacPherson, S. E. (2016) · Behavior Research Methods · doi:10.3758/s13428-016-0750-0 · Cited by 33

Automatic targeted-domain spatiotemporal event detection in twitter

Hua, T., Chen, F., Zhao, L., Lu, C., & Ramakrishnan, N. (2016) · GeoInformatica · doi:10.1007/s10707-016-0263-0 · Cited by 33

Subthalamic Nucleus Deep Brain Stimulation Does Not Modify the Functional Deficits or Axonopathy Induced by Nigrostriatal α-Synuclein Overexpression

Fischer, D. L., Manfredsson, F. P., Kemp, C. J., Cole-Strauss, A., Lipton, J. W., Duffy, M. F., Polinski, N. K., Steece‐Collier, K., Collier, T. J., Gombash, S. E., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-16690-x · Cited by 33

Visual mental imagery influences attentional guidance in a visual-search task

Moriya, J. (2018) · Attention Perception & Psychophysics · doi:10.3758/s13414-018-1520-0 · Cited by 33

Exploring the Influence of Haptic and Olfactory Cues of a Virtual Donut on Satiation and Eating Behavior

Li, B. J., & Bailenson, J. N. (2017) · PRESENCE Virtual and Augmented Reality · doi:10.1162/pres_a_00300 · Cited by 33

The Role of Managerial Commitment and TPM Implementation Strategies in Productivity Benefits

Díaz-Reza, J. R., García-Alcaráz, J. L., Avelar-Sosa, L., Mendoza-Fong, J. R., Diez-Muro, J. C. S., & Blanco‐Fernández, J. (2018) · Applied Sciences · doi:10.3390/app8071153 · Cited by 33

Single Cell Profiling Identifies Key Pathways Expressed by iPSCs Cultured in Different Commercial Media

Daniszewski, M., Nguyen, Q. H., Chy, H. S., Singh, V., Crombie, D. E., Kulkarni, T., Liang, H. H., Sivakumaran, P., Lidgerwood, G. E., Hernández, D., et al. (2018) · iScience · doi:10.1016/j.isci.2018.08.016 · Cited by 31

Quantitative Determination of Cd in Soil Using Laser-Induced Breakdown Spectroscopy in Air and Ar Conditions

Liu, X., Liu, F., Huang, W., Peng, J., Shen, T., & He, Y. (2018) · Molecules · doi:10.3390/molecules23102492 · Cited by 33

Examining the impact of error estimation on the effects of self-controlled feedback

Barros, J. A. D. C., Yantha, Z. D., Carter, M. J., Hussien, J., & Ste‐Marie, D. M. (2018) · Human Movement Science · doi:10.1016/j.humov.2018.12.002 · Cited by 33

Impact of the Revisit of Thermal Infrared Remote Sensing Observations on Evapotranspiration Uncertainty—A Sensitivity Study Using AmeriFlux Data

Guillevic, P., Olioso, A., Hook, S. J., Fisher, J. B., Lagouarde, J., & Vermote, E. F. (2019) · Remote Sensing · doi:10.3390/rs11050573 · Cited by 33

Data science: Use median absolute deviation instead of z-score to detect outliers

Lin, H. (2019)

Detection of outliersPreprint

Velarde, S. A. (2026) · OSF Preprints (OSF Preprints)

How not to MISS an outlier: comparing three classic univariate methods and introducing a new one, the MAD–IQR–SD Simultaneous (MISS).Preprint

Pech, G. P., Caspar, É. A., Amerio, P., Cleeremans, A., Leys, C., Leys, C., & Vaccaro, N. (2026) · doi:10.31234/osf.io/2r9yw_v1

Robustness of sample mean and sample median under restrictions on outliers

Zielinski, R. J. (1987) · Applicationes Mathematicae · doi:10.4064/am-19-2-239-240 · Cited by 6

Outlier Tests in Sample Surveys

Namkyung, P., & Lee, J. S. (2000) · Communications for Statistical Applications and Methods