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

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The Influence Curve and Its Role in Robust Estimation

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Alternatives to the Median Absolute Deviation

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Methods for dealing with reaction time outliers.

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Alternatives to the Median Absolute Deviation

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Outliers detection and treatment: a review.

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Handbook of Research Methods. in Social and Personality Psychology

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

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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

Quantifying dissipation in actomyosin networks

Floyd, C., Papoian, G. A., & Jarzynski, C. (2019) · Interface Focus · doi:10.1098/rsfs.2018.0078 · Cited by 27

The interplay between movement, morphology and dispersal in Tetrahymena ciliates

Pennekamp, F., Clobert, J., & Schtickzelle, N. (2019) · PeerJ · doi:10.7717/peerj.8197 · Cited by 28

Muscle strength, not age, explains unique variance in echo intensity

Bali, A., Harmon, K. K., Burton, A. M., Phan, D. C., Mercer, N. E., Lawless, N. W., & Stock, M. S. (2020) · Experimental Gerontology · doi:10.1016/j.exger.2020.111047 · Cited by 28

Cross-Situational Word Learning in Two Foreign Languages: Effects of Native Language and Perceptual Difficulty

Tuninetti, A., Mulak, K. E., & Escudero, P. (2020) · Frontiers in Communication · doi:10.3389/fcomm.2020.602471 · Cited by 29

I Am Looking for Your Mind: Pupil Dilation Predicts Individual Differences in Sensitivity to Hints of Human-Likeness in Robot Behavior

Marchesi, S., Bossi, F., Ghiglino, D., Tommaso, D. D., & Wykowska, A. (2021) · Frontiers in Robotics and AI · doi:10.3389/frobt.2021.653537 · Cited by 29

Preferred auditory temporal processing regimes and auditory-motor synchronization

Kern, P., Assaneo, M. F., Endres, D., Poeppel, D., & Rimmele, J. M. (2021) · Psychonomic Bulletin & Review · doi:10.3758/s13423-021-01933-w · Cited by 30

Revealing a New Vulnerability of Distributed State Estimation: A Data Integrity Attack and an Unsupervised Detection Algorithm

Shefaei, A., Mohammadpourfard, M., Mohammadi‐Ivatloo, B., & Weng, Y. (2021) · IEEE Transactions on Control of Network Systems · doi:10.1109/tcns.2021.3091631 · Cited by 28

Estimated prevalence of eating disorders in Malaysia based on a diagnostic screen

Chua, S. N., Fitzsimmons‐Craft, E. E., Austin, S. B., Wilfley, D. E., & Taylor, C. B. (2022) · International Journal of Eating Disorders · doi:10.1002/eat.23711 · Cited by 34

Estimating the time since deposition (TsD) in saliva stains using temporal changes in microbial markers

Wang, J., Cheng, X., Zhang, J., Liu, Z., Cheng, F., Yan, J., & Zhang, G. (2022) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2022.102747 · Cited by 28

End-to-End Data Quality Assessment Using Trust for Data Shared IoT Deployments

Byabazaire, J., O’Hare, G. M. P., & Delaney, D. T. (2022) · IEEE Sensors Journal · doi:10.1109/jsen.2022.3203853 · Cited by 31

Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations

Pasik, A., Gruber, A., Preimesberger, W., Santis, D. D., & Dorigo, W. A. (2023) · Geoscientific model development · doi:10.5194/gmd-16-4957-2023 · Cited by 35

Words in larger font are perceived as more important: explaining the belief that font size affects memory

Luna, K., Nogueira, M., & Albuquerque, P. B. (2018) · Memory · doi:10.1080/09658211.2018.1529797 · Cited by 28

Flow States and Associated Changes in Spatial and Temporal Processing

Sinnett, S., Jaeger, J., Singer, S. M., & Philippe, R. A. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.00381 · Cited by 28

A plausible link between the time-on-task effect and the sequential task effect

Mangin, T., Audiffren, M., Lorcery, A., Mirabelli, F., Benraiss, A., & André, N. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.998393 · Cited by 30

Performance of multiple neural networks in predicting lower limb joint moments using wearable sensors

Altai, Z., Boukhennoufa, I., Zhai, X., Phillips, A., Moran, J., & Liew, B. X. W. (2023) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2023.1215770 · Cited by 27

Detecting potential outliers in longitudinal data with time-dependent covariates

Mramba, L. K., Liu, X., Lynch, K. F., Yang, J., Aronsson, C. A., Hummel, S., Norris, J. M., Virtanen, S. M., Hakola, L., Uusitalo, U. M., et al. (2024) · European Journal of Clinical Nutrition · doi:10.1038/s41430-023-01393-6 · Cited by 27

Characterization of stratospheric particle size distribution uncertainties using SAGE II and SAGE III/ISS extinction spectra

Knepp, T. N. N., Kovilakam, M., Thomason, L. W., & Miller, S. J. (2024) · Atmospheric measurement techniques · doi:10.5194/amt-17-2025-2024 · Cited by 27

Noninvasive prognostic classification of ITH in HCC with multi-omics insights and therapeutic implications

Xie, Y., Wang, F., Wei, J., Shen, Z., Song, X., Wang, Y., Chen, H., Tao, L., Zheng, J., Lin, L., et al. (2025) · Science Advances · doi:10.1126/sciadv.ads8323 · Cited by 27

Error and anomaly detection for intra-participant time-series data

Mullineaux, D. R., & Irwin, G. (2017) · International Biomechanics · doi:10.1080/23335432.2017.1348913 · Cited by 27

Automated tracing of helical assemblies from electron cryo-micrographs

Huber, S. T., Kuhm, T., & Sachse, C. (2017) · Journal of Structural Biology · doi:10.1016/j.jsb.2017.11.013 · Cited by 27

Outlier removal in facial surface electromyography through Hampel filtering technique

Bhowmik, S., Jelfs, B., Arjunan, S. P., & Kumar, D. (2017) · IEEE Life Sciences Conference (LSC) · doi:10.1109/lsc.2017.8268192 · Cited by 27

Rule based classification of neurodegenerative diseases using data driven gait features

Gupta, K., Khajuria, A., Chatterjee, N., Joshi, P., & Joshi, D. (2018) · Health and Technology · doi:10.1007/s12553-018-0274-y · Cited by 27

A multiobjective optimization model for machining quality in the AISI 12L14 steel turning process using fuzzy multivariate mean square error

GAUDENCIO, J. H. D., de Almeida, F. A., Turrioni, J. B., Quinino, R. D. C., Balestrassi, P. P., & de Paiva, A. P. (2019) · Precision Engineering · doi:10.1016/j.precisioneng.2019.01.001 · Cited by 27

Social structure and spatial distribution of bottlenose dolphins ( Tursiops truncatus ) along the Croatian Adriatic coast

Pleslić, G., Rako‐Gospić, N., Miočić‐Stošić, J., Vučur, T. B., Radulović, M., Mackelworth, P. C., Frleta‐Valić, M., & Holcer, D. (2019) · Aquatic Conservation Marine and Freshwater Ecosystems · doi:10.1002/aqc.3213 · Cited by 27

A cost-effective and non-invasive system for sleep and vital signs monitoring using passive RFID tags

Hussain, Z., Sagar, S., Zhang, W. E., & Sheng, Q. Z. (2019) · EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous) · doi:10.1145/3360774.3360797 · Cited by 26

Outlier Detection in Object Counting based on Hue and Distance Transform using Median Absolute Deviation (MAD)

Fitriyah, H., & Budi, A. S. (2019) · International Conference on Sustainable Information Engineering and Technology (SIET) · doi:10.1109/siet48054.2019.8985993 · Cited by 27

Balancing Between Goal-Directed and Habitual Responding Following Acute Stress

Hartogsveld, B., van Ruitenbeek, P., Quaedflieg, C. W. E. M., & Smeets, T. (2020) · Experimental Psychology (formerly Zeitschrift für Experimentelle Psychologie) · doi:10.1027/1618-3169/a000485 · Cited by 32

Re-evaluating Scythian lifeways: Isotopic analysis of diet and mobility in Iron Age Ukraine

Miller, A. V., Johnson, J. A., Владимирович, М. С., Gerling, C., Litvinova, L., Andrukh, S., Toschev, G., Zech, J., le Roux, P., Makarewicz, C. A., et al. (2021) · PLoS ONE · doi:10.1371/journal.pone.0245996 · Cited by 28

Thinking Inconsistently

Petrović, M., & Žeželj, I. (2021) · European Journal of Psychological Assessment · doi:10.1027/1015-5759/a000645 · Cited by 12

Age-related changes in ongoing thought relate to external context and individual cognition

Turnbull, A. G., Poerio, G. L., Ho, N. S. P., Martinon, L. M., Riby, L. M., Lin, F. V., Jefferies, E., & Smallwood, J. (2021) · Consciousness and Cognition · doi:10.1016/j.concog.2021.103226 · Cited by 29

Relational thinking: An overlooked component of executive functioning

Starr, A., Leib, E. R., Younger, J. W., Uncapher, M. R., & Bunge, S. A. (2022) · Developmental Science · doi:10.1111/desc.13320 · Cited by 33

The pupillometry of the possible: an investigation of infants' representation of alternative possibilities

Cesana‐Arlotti, N., Varga, B., & Téglás, E. (2022) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2021.0343 · Cited by 28

Entorhinal grid-like codes and time-locked network dynamics track others navigating through space

Wagner, I. C., Graichen, L. P., Todorova, B., Lüttig, A., Omer, D. B., Stangl, M., & Lamm, C. (2023) · Nature Communications · doi:10.1038/s41467-023-35819-3 · Cited by 33

Applying Machine Learning to Estimate the Effort and Duration of Individual Tasks in Software Projects

Sousa, A., Veloso, D. T., Gonçalves, H., Faria, J. P., Mendes‐Moreira, J., Graça, R., Gomes, D., Castro, R. S. E., & Henriques, P. C. (2023) · IEEE Access · doi:10.1109/access.2023.3307310 · Cited by 27

Automatic Segmentation and Quantification of White and Brown Adipose Tissues from PET/CT Scans

Hussein, S., Green, A., Watane, A., Reiter, D. A., Chen, X., Papadakis, G. Z., Wood, B. J., Cypess, A. M., Osman, M., & Bağcı, U. (2016) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2016.2636188 · Cited by 27

Individual differences influence two-digit number processing, but not their analog magnitude processing: a large-scale online study

Huber, S., Nuerk, H., Reips, U., & Soltanlou, M. (2017) · Psychological Research · doi:10.1007/s00426-017-0964-5 · Cited by 25

An individual-based model for sablefish: Exploring the connectivity between potential spawning and nursery grounds in the Gulf of Alaska

Gibson, G. A., Stockhausen, W. T., Coyle, K. O., Hinckley, S. L., Parada, C., Hermann, A. J., Doyle, M. J., & Ladd, C. (2018) · Deep Sea Research Part II Topical Studies in Oceanography · doi:10.1016/j.dsr2.2018.05.015 · Cited by 28

Exploring and cleaning big data with random sample data blocks

Salloum, S., Huang, J. Z., & He, Y. (2019) · Journal Of Big Data · doi:10.1186/s40537-019-0205-4 · Cited by 27

Consumption of whole purple and regular wheat modestly improves metabolic markers in adults with elevated high-sensitivity C-reactive protein: a randomised, single-blind parallel-arm study

Gamel, T. H., Abdel‐Aal, E. M., Tucker, A. J., Paré, S., Faughnan, K., O'Brien, C., Dykun, A., Rabalski, I., Pickard, M. D., & Wright, A. J. (2020) · British Journal Of Nutrition · doi:10.1017/s0007114520002275 · Cited by 29

Noninvasive pulmonary artery pressure monitoring by EIT: a model-based feasibility study

Proença, M., Braun, F., Solà, J., Thiran, J., & Lemay, M. (2016) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-016-1570-1 · Cited by 27

Taking PISA Seriously: How Accurate are Low Stakes Exams?

Akyol, Ş. P., Krishna, K., & Wang, J. (2018) · National Bureau of Economic Research · doi:10.3386/w24930 · Cited by 27

Promoting Acceptance and Adherence to Noninvasive Ventilation in Chronic Obstructive Pulmonary Disease: A Randomized Controlled Trial.

Volpato, E., Banfi, P., & Pagnini, F. (2022) · Psychosomatic Medicine · doi:10.1097/psy.0000000000001053 · Cited by 24

Association of cardiometabolic multimorbidity and adherence to a healthy lifestyle with incident dementia: a large prospective cohort study

Xiong, S., Hou, N., Tang, F., Li, J., & Deng, H. (2023) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-023-01186-8 · Cited by 29

A unified approach to investigating 4 dpf zebrafish larval behaviour through a standardised light/dark assay

Hillman, C., Kearn, J., & Parker, M. O. (2024) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2024.111084 · Cited by 26

Assessing global sustainability performance, imbalance, and coordination over space and time

Xu, Z., Chen, X., Jiang, Q., Wu, X., Bhattarai, N., Mullen, J., Li, Z. B., Gurney, G. G., Li, S., Li, C., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-64219-y · Cited by 26

For your eyes only: effect of confederate’s eye level on reach-to-grasp action

Quesque, F., & Coello, Y. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.01407 · Cited by 26

Sensitivity analysis of an outlier-aware k-means clustering algorithm

Olukanmi, P., & Twala, B. (2017) · Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa (SAUPEC/RobMech/PRASA) · doi:10.1109/robomech.2017.8261125 · Cited by 26

Inter-individual physiological variation in responses to environmental variation and environmental change: Integrating across traits and time

Tanner, R. L., & Dowd, W. W. (2019) · Comparative Biochemistry and Physiology Part A Molecular & Integrative Physiology · doi:10.1016/j.cbpa.2019.110577 · Cited by 26

That’s not fair! The effects of teacher justice and academic achievement on Self and Other’s resistant agency

Mameli, C., Caricati, L., & Molinari, L. (2019) · British Journal of Educational Psychology · doi:10.1111/bjep.12335 · Cited by 26

Effect of an e-retailer’s product category and social media platform selection on perceived quality of e-retail products

Vazquez, E. E. (2020) · Electronic Markets · doi:10.1007/s12525-020-00394-8 · Cited by 29

Phasic and tonic serotonin modulate alarm reactions and post‐exposure behavior in zebrafish

Lima, M. G., Pyterson, M. P., Silva, R. X. D. C., Gomes, G. C. V., Rocha, S. P., Herculano, A. M., Rosemberg, D. B., & Maximino, C. (2020) · Journal of Neurochemistry · doi:10.1111/jnc.14978 · Cited by 26

Bilingualism and Processing Speed in Typically Developing Children and Children With Developmental Language Disorder

Park, J. S., Miller, C., Sanjeevan, T., van Hell, J. G., Weiss, D. J., & Mainela‐Arnold, E. (2020) · Journal of Speech Language and Hearing Research · doi:10.1044/2020_jslhr-19-00403 · Cited by 26

Hippocampal stiffness in mesial temporal lobe epilepsy measured with MR elastography: Preliminary comparison with healthy participants

Huesmann, G., Schwarb, H. D., Smith, D. R., Pohlig, R. T., Anderson, A. T., McGarry, M., Paulsen, K. D., Wszalek, T., Sutton, B. P., & Johnson, C. L. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102313 · Cited by 26

Reusing Ambient Light to Recognize Hand Gestures

Kaholokula, M.-D. A. (2016) · Cited by 26

Refining the Joint 3D Processing of Terrestrial and UAV Images Using Quality Measures

Farella, E. M., Torresani, A., & Fabio Remondino, A. (2020) · Remote Sensing · doi:10.3390/rs12182873 · Cited by 26

Non-invasive pulmonary artery pressure estimation by electrical impedance tomography in a controlled hypoxemia study in healthy subjects

Proença, M., Braun, F., Lemay, M., Solà, J., Adler, A., Riedel, T., Messerli, F. H., Thiran, J., Rimoldi, S. F., & Rexhaj, E. (2020) · Scientific Reports · doi:10.1038/s41598-020-78535-4 · Cited by 26

The COTUR project: remote sensing of offshore turbulence for wind energy application

Cheynet, E., Flügge, M., Reuder, J., Jakobsen, J. B., Heggelund, Y., Svardal, B., Garfias, P. S., Obhrai, C., Daniotti, N., Berge, J., et al. (2021) · Atmospheric measurement techniques · doi:10.5194/amt-14-6137-2021 · Cited by 26

Kaufman Domains of Creativity Scale: Relationship to Occupation and Measurement Invariance across Gender

Miroshnik, K. G., Shcherbakova, O., & Kaufman, J. C. (2021) · Creativity Research Journal · doi:10.1080/10400419.2021.1953823 · Cited by 26

Dose-Response Effects of Acute Aerobic Exercise Intensity on Inhibitory Control in Children With Attention Deficit/Hyperactivity Disorder

Tsai, Y.-J., Hsieh, S., Huang, C., & Hung, T. (2021) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2021.617596 · Cited by 32

Plurality in the Measurement of Social Media Use and Mental Health: An Exploratory Study Among Adolescents and Young Adults

Petalas, D. P., Konijn, E. A., Johnson, B. K., Veldhuis, J., de Vaate, N. A. J. D. B., Burgers, C. F., Droog, E., Międzobrodzka, E., Bálint, K., & van de Schoot, R. (2021) · Social Media + Society · doi:10.1177/20563051211035353 · Cited by 31

Leveraging sequential information from multivariate behavioral sensor data to predict the moment of calving in dairy cattle using deep learning

Liseune, A., den Poel, D. V., Hut, P. R., Eerdenburg, F. J. C. M. V., & Hostens, M. (2021) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2021.106566 · Cited by 30

Pupillometry and the vigilance decrement: Task‐evoked but not baseline pupil measures reflect declining performance in visual vigilance tasks

Martin, J. T., Whittaker, A. H., & Johnston, S. J. (2022) · European Journal of Neuroscience · doi:10.1111/ejn.15585 · Cited by 28

Do jigsaw classrooms improve learning outcomes? Five experiments and an internal meta-analysis.

Stanczak, A., Darnon, C., Robert, A., Demolliens, M., Sanrey, C., Bressoux, P., Huguet, P., Buchs, C., & Butera, F. (2022) · Journal of Educational Psychology · doi:10.1037/edu0000730 · Cited by 49

You’re in for a Bumpy Ride! Uneven Terrain Increases Cybersickness While Navigating with Head Mounted Displays

Ang, S. P., & Quarles, J. P. (2022) · IEEE Conference on Virtual Reality and 3D User Interfaces (VR) · doi:10.1109/vr51125.2022.00062 · Cited by 28

Micro-firms way to succeed: How owners manage people

Rodrigues, A. C., Carvalho, H., Caetano, A., & Santos, S. C. (2022) · Journal of Business Research · doi:10.1016/j.jbusres.2022.05.062 · Cited by 29

Hybrid D1DCnet Using Forehead iPPG for Continuous and Noncontact Blood Pressure Measurement

Li, Y., Wei, M., Chen, Q., Xing, Z., Li, H., Wang, H., & Luo, J. (2022) · IEEE Sensors Journal · doi:10.1109/jsen.2022.3230210 · Cited by 27

Outliers detection method of multiple measuring points of parameters in power plant units

Qi, M., Fu, Z., & Chen, F. (2015) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2015.04.008 · Cited by 26

Drinker Prototype Alteration and Cue Reminders as Strategies in a Tailored Web-Based Intervention Reducing Adults’ Alcohol Consumption: Randomized Controlled Trial

van Lettow, B., de Vries, H., Alex Burdorf, A., Boon, B. J. F., & van Empelen, P. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.3551 · Cited by 28

Are the most popular users always trustworthy? The case of Yelp

Pranata, I., & Susilo, W. (2016) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2016.09.005 · Cited by 26

The impact of rapid release cycles on the integration delay of fixed issues

da Costa, D. A., McIntosh, S., Treude, C., Kulesza, U., & Hassan, A. E. (2017) · Empirical Software Engineering · doi:10.1007/s10664-017-9548-7 · Cited by 26

A comparative analysis of response times shows that multisensory benefits and interactions are not equivalent

Innes, B. R., & Otto, T. U. (2019) · Scientific Reports · doi:10.1038/s41598-019-39924-6 · Cited by 24

Control Charts for Monitoring Process Capability Index Using Median Absolute Deviation for Some Popular Distributions

Aslam, M., Rao, G. S., AL-Marshadi, A. H., Ahmad, L., & Jun, C. (2019) · Processes · doi:10.3390/pr7050287 · Cited by 26

Evaluating Patient Readmission Risk: A Predictive Analytics Approach

Choudhury, A., & Greene, C. (2018) · American Journal of Engineering and Applied Sciences · doi:10.3844/ajeassp.2018.1320.1331 · Cited by 29

Stability of Lifestyle Behavior – The Answer to Successful Cognitive Aging? A Comparison of Nuns, Monks, Master Athletes and Non-active Older Adults

Schott, N., & Krull, K. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.01347 · Cited by 27

A systematic review and meta‐analysis of the association of neighborhood ethnic‐racial concentrations and adolescent behaviour problems in the U.S.

White, R. M. B., Pasco, M. C., Korous, K. M., & Causadías, J. M. (2019) · Journal of Adolescence · doi:10.1016/j.adolescence.2019.12.005 · Cited by 30

Photosynthetic energy conversion efficiency in the West Antarctic Peninsula

Sherman, J., Gorbunov, M. Y., Schofield, O., & Falkowski, P. G. (2020) · Limnology and Oceanography · doi:10.1002/lno.11562 · Cited by 26

Knowledge Attributions and Behavioral Predictions

Turri, J. (2016) · Cognitive Science · doi:10.1111/cogs.12469 · Cited by 25

The impact of switching to a rapid release cycle on the integration delay of addressed issues

da Costa, D. A., McIntosh, S., Kulesza, U., & Hassan, A. E. (2016) · International Conference on Mining Software Repositories (MSR) · doi:10.1145/2901739.2901764 · Cited by 25

Full-field measurement of micromotion around a cementless femoral stem using micro-CT imaging and radiopaque markers

Camine, V. M., Rüdiger, H. A., Pioletti, D. P., & Terrier, A. (2016) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2016.10.029 · Cited by 25

Autoregressive-based outlier algorithm to detect money laundering activities

Kannan, S., & Somasundaram, K. (2017) · Journal of Money Laundering Control · doi:10.1108/jmlc-07-2016-0031 · Cited by 25

A dynamic allosteric pathway underlies Rad50 ABC ATPase function in DNA repair

Boswell, Z. K., Rahman, S., Canny, M. D., & Latham, M. P. (2018) · Scientific Reports · doi:10.1038/s41598-018-19908-8 · Cited by 25

Noise level penalizing robust Gaussian process regression for NIR spectroscopy quantitative analysis

Liu, C., Yang, S. X., Li, X., Li-juan, X., & Deng, L. (2020) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2020.104014 · Cited by 25

High-rate GPS positioning for tracing anthropogenic seismic activity: The 29 January 2019 mining tremor in Legnica- Głogów Copper District, Poland

Kudłacik, I., Kapłon, J., Lizurek, G., Crespi, M., & Kurpiński, G. (2020) · Measurement · doi:10.1016/j.measurement.2020.108396 · Cited by 25

Trait anxiety does not correlate with metacognitive confidence or reminder usage in a delayed intentions task

Kirk, P. A., Robinson, O. J., & Gilbert, S. J. (2020) · Quarterly Journal of Experimental Psychology · doi:10.1177/1747021820970156 · Cited by 29

Value Representations in the Rodent Orbitofrontal Cortex Drive Learning, not ChoicePreprint

Miller, K. J., Botvinick, M., & Brody, C. D. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/245720 · Cited by 27

Alpha power decrease in quantitative EEG detects development of cerebral infarction after subarachnoid hemorrhage early

Mueller, T. M., Gollwitzer, S., Hopfengärtner, R., Rampp, S., Lang, J., Stritzelberger, J., Madžar, D., Reindl, C., Sprügel, M. I., Onugoren, M. D., et al. (2021) · Clinical Neurophysiology · doi:10.1016/j.clinph.2021.03.005 · Cited by 25

Modifying food items valuation and weight with gamified executive control training

Najberg, H., Rigamonti, M., Mouthon, M., & Spierer, L. (2021) · Royal Society Open Science · doi:10.1098/rsos.191288 · Cited by 24

Skin conductance response to trauma interview as a candidate biomarker of trauma and related psychopathology in youth resettled as refugees

Grasser, L. R., Saad, B., Bazzi, C., Wanna, C., Suhaiban, H. A., Mammo, D. F., Jovanović, T., & Javanbakht, A. (2022) · European Journal of Psychotraumatology · doi:10.1080/20008198.2022.2083375 · Cited by 25

Megalopolitan-scale ground deformation along metro lines in the Guangdong-Hong Kong-Macao Greater Bay Area, China, revealed by MT-InSAR

Zhang, B., Liao, X., Zhang, J., Xiong, S., Wang, C., Wu, S., Zhu, C., Zhu, J., Qin, X., & Li, Q. (2023) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2023.103432 · Cited by 25

Some habits are more work than others: Deliberate self‐regulation strategy use increases with behavioral complexity, even for established habits

Saunders, B., & More, K. R. (2024) · Journal of Personality · doi:10.1111/jopy.12926 · Cited by 25

An unsupervised approach for gait-based authentication

Cola, G., Avvenuti, M., Vecchio, A., Yang, G., & Lo, B. P. L. (2015) · Wearable and Implantable Body Sensor Networks · doi:10.1109/bsn.2015.7299423 · Cited by 25

Terpene arms race in the Seiridium cardinale – Cupressus sempervirens pathosystem

Achotegui-Castells, A., Rocca, G. D., Llusià, J., Danti, R., Barberini, S., Bouneb, M., Simoni, S., Michelozzi, M., & Peñuelas, J. (2016) · Scientific Reports · doi:10.1038/srep18954 · Cited by 25

Transfer after process-based object-location memory training in healthy older adults.

Zimmermann, K., von Bastian, C. C., Röcke, C., Martin, M., & Eschen, A. (2016) · Psychology and Aging · doi:10.1037/pag0000123 · Cited by 28

Impact of age and vector construct on striatal and nigral transgene expression

Polinski, N. K., Manfredsson, F. P., Benskey, M. J., Fischer, D. L., Kemp, C. J., Steece‐Collier, K., Sandoval, I. M., Paumier, K. L., & Sortwell, C. E. (2016) · Molecular Therapy — Methods & Clinical Development · doi:10.1038/mtm.2016.82 · Cited by 25

Lost in Time and Space: States of High Arousal Disrupt Implicit Acquisition of Spatial and Sequential Context Information

Maran, T., Sachse, P., Martini, M., Weber, B., Pinggera, J., Zuggal, S., & Furtner, M. (2017) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2017.00206 · Cited by 25

Multi-Phenotype Association Decomposition: Unraveling Complex Gene-Phenotype Relationships

Weighill, D. A., Jones, P. C., Bleker, C., Ranjan, P., Shah, M. B., Zhao, N., Martin, M. Z., DiFazio, S. P., Macaya‐Sanz, D., Schmutz, J., et al. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00417 · Cited by 25

Optimizing User Interface Layouts via Gradient Descent

Duan, P., Wierzynski, C., & Nachman, L. (2020) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376589 · Cited by 25

Transcriptome sequencing and molecular markers discovery in the gonads of Portunus sanguinolentus

Zhang, Y., Miao, G., Wu, Q., Lin, F., You, C., Wang, S., Aweya, J. J., & Ma, H. (2018) · Scientific Data · doi:10.1038/sdata.2018.131 · Cited by 24

Pre-Registration in Social Psychology—a Discussion and Suggested TemplatePreprint

Veer, A. V. '., & Giner‐Sorolla, R. (2016) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/4frms · Cited by 31

PSHG-TISS: A collection of polarization-resolved second harmonic generation microscopy images of fixed tissues

Hristu, R., Stanciu, S. G., Dumitru, A. V., Eftimie, L. G., Paun, B., Tranca, D. E., Gheorghita, P., Costache, M., & Stanciu, G. A. (2022) · Scientific Data · doi:10.1038/s41597-022-01477-1 · Cited by 25

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