The Probable Error of a Mean

Assessing Changes in Exceptional Rainfall in Portugal Using ERA5-Land Reanalysis Data (1981/1982–2022/2023)

Espinosa, L. Á., Portela, M. M., & Gharbia, S. S. (2024) · Water · doi:10.3390/w16050628 · Cited by 18

Instructed to Bias: Instruction-Tuned Language Models Exhibit Emergent Cognitive Bias

Itzhak, I., Stanovsky, G., Rosenfeld, N., & Belinkov, Y. (2024) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00673 · Cited by 42

Using Cluster Analysis to Segment Students Based on Self-Reported Emotionally Intelligent Leadership Behaviors

Facca, T. M., & Allen, S. J. (2011) · Journal of Leadership Education · doi:10.12806/v10/i2/rf4 · Cited by 21

Automatic selection of near-native protein-ligand conformations using a hierarchical clustering and volunteer computing

Estrada, T., Armen, R. S., & Taufer, M. (2010) · ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB) · doi:10.1145/1854776.1854807 · Cited by 16

Plurality of Type A evaluations of uncertainty

Possolo, A. M., & Pintar, A. L. (2017) · Metrologia · doi:10.1088/1681-7575/aa7e4a · Cited by 16

A Framework for Spatial-Temporal Trajectory Cluster Analysis Based on Dynamic Relationships

Portugal, I. D. S., Alencar, P., & Cowan, D. D. (2020) · IEEE Access · doi:10.1109/access.2020.3023376 · Cited by 16

Multimodal Mixed Reality Impact on a Hand Guiding Task with a Holographic Cobot

Rivera, A., Kildal, J., & Lazkano, E. (2020) · Multimodal Technologies and Interaction · doi:10.3390/mti4040078 · Cited by 16

Population ecology of a California endemic: Speyeria adiaste clemencei

Zaman, K., Tenney, C. R., Rush, C. E., & Hill, R. I. (2015) · Journal of Insect Conservation · doi:10.1007/s10841-015-9797-y · Cited by 16

Hemithoracic Radiotherapy After Extrapleural Pneumonectomy for Malignant Pleural Mesothelioma: A Dosimetric Comparison of Two Well-Described Techniques

Hill‐Kayser, C. E., Avery, S., Mesina, C. F., James, P., Friedberg, J. S., Cengel, K. A., Lin, L. L., Hahn, S. M., & Rengan, R. (2009) · Journal of Thoracic Oncology · doi:10.1097/jto.0b013e3181b9eb85 · Cited by 16

Nonparametric Methods for Molecular Biology

Wittkowski, K. M., & Song, T. (2009) · Methods in molecular biology · doi:10.1007/978-1-60761-580-4_2 · Cited by 17

Using an Artificial Neural Network for Predicting Embedded Software Development Effort

Iwata, K., Anan, Y., Nakashima, T., & Ishii, N. (2009) · ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) · doi:10.1109/snpd.2009.49 · Cited by 16

Lethal synergistic effect of cigarette smoke and saliva in an in vitro model: does saliva have a role in the development of oral cancer?

Hershkovich, O., de la Oliva, J., & Nagler, R. M. (2004) · European Journal of Cancer · doi:10.1016/j.ejca.2004.03.027 · Cited by 16

Chemical Structure of Model Substances Related to Their Gushing-Inducing and -suppressing Activity

Christian, M., Titze, J., & Ilberg, V. (2011) · Journal of the American Society of Brewing Chemists · doi:10.1094/asbcj-2011-0716-01 · Cited by 16

Sample Size Estimation for Random-effects Models

Weichenthal, S., Baumgartner, J., & Hanley, J. A. (2017) · Epidemiology · doi:10.1097/ede.0000000000000727 · Cited by 16

Diagnosis of Sustainable Business Strategies Implemented by Chilean Construction Companies

Giannoni, C., Alarcón, L. F., & Vera, S. (2017) · Sustainability · doi:10.3390/su10010082 · Cited by 16

Confocal Raman Microscopy for in Situ Measurement of Phospholipid–Water Partitioning into Model Phospholipid Bilayers within Individual Chromatographic Particles

Kitt, J. P., Bryce, D. A., Minteer, S. D., & Harris, J. M. (2018) · Analytical Chemistry · doi:10.1021/acs.analchem.8b01452 · Cited by 16

Hidden partners: Using cross‐docking calculations to predict binding sites for proteins with multiple interactions

Lagarde, N., Carbone, A., & Sacquin‐Mora, S. (2018) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.25506 · Cited by 15

On estimating the epistemic probability of realizing Q = Pfus/Paux larger than a specified lower bound in ITER

Kardaun, O. (2002) · Nuclear Fusion · doi:10.1088/0029-5515/42/7/307 · Cited by 16

Comparisons of approximations to the percentiles of the t , x 2 ,and F distributions

Sahai, H., & Thompson, W. O. (1974) · Journal of Statistical Computation and Simulation · doi:10.1080/00949657408810073 · Cited by 16

Active transcription of the selenium-dependent glutathione peroxidase gene in selenium-deficient rats

Chang, M., & Reddy, C. C. (1991) · Biochemical and Biophysical Research Communications · doi:10.1016/0006-291x(91)92099-6 · Cited by 16

Digital integration of granulocyte aggregation responses

Craddock, P. R., White, J. G., Weisdorf, D. J., & Hammerschmidt, D. E. (1980) · Inflammation · doi:10.1007/bf00916049 · Cited by 16

Letters to the Editor

(1972) · The American Statistician · doi:10.1080/00031305.1972.10478957 · Cited by 16

GPCR molecular dynamics forecasting using recurrent neural networks

López-Correa, J. M., König, C., & Vellido, A. (2023) · Scientific Reports · doi:10.1038/s41598-023-48346-4 · Cited by 16

The date ofSir Thomas More

Craig, H. (2013) · Cambridge University Press eBooks · doi:10.1017/sso9781107300699.003 · Cited by 15

Brief Spanish Zung Self-Rating Anxiety Scale: Dimensionality, Internal Consistency, Nomological Validity, and Differential Item Functioning Among Chronic Obstructive Pulmonary Disease Patients in Colombia

Campo‐Arias, A., Blanco-Ortega, J. D., & Pedrozo‐Pupo, J. C. (2021) · Journal of Nursing Measurement · doi:10.1891/jnm-d-20-00125 · Cited by 16

The intricate triangular interaction between protective microbe, pathogen and host determines fitness of the metaorganism

Griem-Krey, H., Petersen, C., Hamerich, I. K., & Hinrich Schulenburg, Y. (2023) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2023.2193 · Cited by 13

A note on “Modelling exchange rate returns: which flexible distribution to use?”

Nadarajah, S., Afuecheta, E., & Chan, S. (2015) · Quantitative Finance · doi:10.1080/14697688.2015.1032997 · Cited by 15

Outdoor Terrestrial Model Ecosystems are suitable to detect pesticide effects on soil fauna: design and method development

Scholz‐Starke, B., Nikolakis, A., Leicher, T., Lechelt‐Kunze, C., Heimbach, F., Theißen, B., Toschki, A., Ratte, H., Schäffer, A., & Roß‐Nickoll, M. (2011) · Ecotoxicology · doi:10.1007/s10646-011-0732-z · Cited by 15

Cross-Correlation-Based, Phase-Domain Spectrum Sensing With Low-Cost Software-Defined Radio Receivers

Kitsunezuka, M., & Pister, K. S. J. (2015) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2015.2407324 · Cited by 15

Investigating small-world and scale-free structure of earthquake networks in Greece

Chorozoglou, D., Papadimitriou, E. E., & Kugiumtzis, D. (2019) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2019.03.018 · Cited by 15

Impact of Uncertainty in the Input Variables and Model Parameters on Predictions of a Long Short Term Memory (LSTM) Based Sales Forecasting Model

Goel, S., & Bajpai, R. (2020) · Machine Learning and Knowledge Extraction · doi:10.3390/make2030014 · Cited by 15

Assessment of Proactive Environmental Initiatives: Evaluation of Efficiency Based on Interval-Scale Data

Mahapatra, S., Pal, R., Hult, G. T. M., & Talluri, S. (2015) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2015.2413938 · Cited by 15

Academic performance assessment using Augmented Reality in engineering degree course

Riera, A. S., Domínguez, E. R., Fonseca, D., & Navarro, I. (2014) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie.2014.7044238 · Cited by 15

Sampling distributions of random electromagnetic fields in mesoscopic or dynamical systems

Arnaut, L. R. (2009) · Physical Review E · doi:10.1103/physreve.80.036601 · Cited by 15

An empirical approach toward the resolution of conflicts in goal-oriented models

Hassine, J., & Amyot, D. (2015) · Software & Systems Modeling · doi:10.1007/s10270-015-0460-6 · Cited by 16

An automated deformable image registration evaluation of confidence tool

Kirby, N., Chen, J., Kim, H., Morin, O., Nie, K., & Pouliot, J. (2016) · Physics in Medicine and Biology · doi:10.1088/0031-9155/61/8/n203 · Cited by 15

What Do We Know?: Simple Statistical Techniques that Help

Nicholls, A. O. (2010) · Methods in molecular biology · doi:10.1007/978-1-60761-839-3_22 · Cited by 15

Introduction to Markov Chains

Bonamente, M. (2016) · Graduate texts in physics · doi:10.1007/978-1-4939-6572-4_15 · Cited by 15

Wrapped: An R package for circular data

Nadarajah, S., & Zhang, Y. (2017) · PLoS ONE · doi:10.1371/journal.pone.0188512 · Cited by 15

DAILY ASSYMETRY OF AIR TEMPERATURE CHANGES IN UKRAINE

Осадчий, В. І., Aguilar, E., Skrynyk, O., Boichuk, D., Sidenko, V., & Skrynyk, O. (2018) · Ukrainian geographical journal · doi:10.15407/ugz2018.03.021 · Cited by 15

Accelerating invasions and the asymptotics of fat-tailed dispersal

Liu, B. R., & Kot, M. (2019) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2019.03.016 · Cited by 15

Automatic seismic wave arrival detection and picking with stationary analysis: Application of the KM2O-Langevin equations

Nakamula, S., Takeo, M., Okabe, Y., & Matsuura, M. (2007) · Earth Planets and Space · doi:10.1186/bf03352719 · Cited by 15

DNA damage benzo[α]pyrene in the liver of mosquito fish Gambusia affinis

Batel, R., Bihari, N., Kureleć, B., & Zahn, R. K. (1985) · The Science of The Total Environment · doi:10.1016/0048-9697(85)90146-9 · Cited by 15

Characteristics of coumarin metabolism by liver microsomes from cobalt-pretreated mice

Legrum, W., & Netter, K. J. (1980) · Xenobiotica · doi:10.3109/00498258009033755 · Cited by 15

320. Comparison of the growth-promoting value for rats of butter fat, of margarine fat and of vegetable oils

Henry, K. M., Kon, S. K., Hilditch, T. P., & Meara, M. L. (1945) · Journal of Dairy Research · doi:10.1017/s0022029900032301 · Cited by 15

359. A note on the effect of the temperature of pre-heating of spray-dried whole milk on the biological value of its proteins

Henry, K. M., & Kon, S. K. (1947) · Journal of Dairy Research · doi:10.1017/s0022029900005021 · Cited by 15

The Use of Chicks for the Biological Assay of Members of the Vitamin B Complex

Coates, M. E., Kon, S. K., & Shepheard, E. E. (1950) · British Journal Of Nutrition · doi:10.1079/bjn19500037 · Cited by 15

Systematic TLE data improvement by neural network for most cataloged resident space objects

Bizalion, H., Guillot, A., Petit, A., & Lucken, R. (2022) · Advances in Space Research · doi:10.1016/j.asr.2022.07.006 · Cited by 14

Steroid hormone-induced wingless ligands tune female intestinal size in Drosophila

Zipper, L., Corominas‐Murtra, B., & Reiff, T. (2025) · Nature Communications · doi:10.1038/s41467-024-55664-2 · Cited by 14

Likelihood ratio calculation for a disputed-utterance analysis with limited available data

Morrison, G. S., Lindh, J., & Curran, J. M. (2013) · Speech Communication · doi:10.1016/j.specom.2013.11.004 · Cited by 14

Cytotechnologist-Attended On-Site Evaluation of Adequacy for Metastatic Disease Involving Bone and Soft Tissue

Olson, M. T., Novak, A., Kirby, J. W., Shahid, H., Boonyaarunnate, T., & Ali, S. Z. (2013) · Acta Cytologica · doi:10.1159/000354079 · Cited by 14

Meta-analysis of archived DNA microarrays identifies genes regulated by hypoxia and involved in a metastatic phenotype in cancer cells

Pierre, M., Hertogh, B. D., Gaigneaux, A., Meulder, B. D., Berger, F., Bareke, E., Michiels, C., & Depiereux, E. (2010) · BMC Cancer · doi:10.1186/1471-2407-10-176 · Cited by 14

Edaphic Ecology and Genetics of the Gabbro-Endemic Shrub Ceanothus roderickii (Rhamnaceae)

Bürge, D. O., & Manos, P. S. (2011) · Madroño · doi:10.3120/0024-9637-58.1.1 · Cited by 14

The Probability that Your Hypothesis Is Correct, Credible Intervals, and Effect Sizes for IR Evaluation

Sakai, T. (2017) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3077136.3080766 · Cited by 14

The roles of contact time and contact pressure on the coalescence of water droplets suspended in concentrated bitumen solutions

Goel, S., Ng, S., Acosta, E., & Ramachandran, A. (2018) · Fuel · doi:10.1016/j.fuel.2018.02.182 · Cited by 14

Chi-Square Distribution: New Derivations and Environmental Application

Semkow, T. M., Freeman, N., Syed, U.-F., Haines, D. K., Bari, A., Khan, A. J., Nishikawa, K., Khan, A. H., Burn, A. G., Li, X., et al. (2019) · Journal of Applied Mathematics and Physics · doi:10.4236/jamp.2019.78122 · Cited by 14

Annual Actual Evapotranspiration Estimation via GIS Models of Three Empirical Methods Employing Remotely Sensed Data for the Peloponnese, Greece, and Comparison with Annual MODIS ET and Pan Evaporation Measurements

Dimitriadou, S., & Nikolakopoulos, K. G. (2021) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi10080522 · Cited by 14

Optimized Synthesis of New Thiosemicarbazide Derivatives with Tuberculostatic Activity

Popovici, C., Pavel, C.-M., Şunel, V., Cheptea, C., Dimitriu, D. G., Dorohoi, D. O., David, D., Cloşca, V., & Popa, M. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms222212139 · Cited by 14

Measurement errors and instrument inaccuracies

Cunningham, M. J. (1981) · Journal of Physics E Scientific Instruments · doi:10.1088/0022-3735/14/8/001 · Cited by 14

Bias in log-transformed frequency distributions

Wilson, B. G., Adams, B. J., & Karney, B. W. (1990) · Journal of Hydrology · doi:10.1016/0022-1694(90)90248-v · Cited by 14

Spontaneous cracking of thermally toughened safety glass Part two: Nickel sulphide inclusions identified in annealed glass

Kasper, A. M., Pyeonglae, N., & Yuan, Z. J. (2018) · Glass Structures & Engineering · doi:10.1007/s40940-018-00092-0 · Cited by 14

Adolescent Violent Behavior

Franke, T. M. (2000) · Journal of Multicultural Social Work · doi:10.1300/j285v08n01_03 · Cited by 14

Decreased physical function in juvenile rheumatoid arthritis

Miller, M. L., Kress, A. M., & Berry, C. A. (1999) · Arthritis & Rheumatism · doi:10.1002/1529-0131(199910)12:5 · Cited by 27

Approximate studentization for Pareto distribution with application to censored data

Wong, A. C. M. (1998) · Statistical Papers · doi:10.1007/bf02925406 · Cited by 14

Glucocorticosteroids for people with alcoholic hepatitis

Pavlov, C. S., Tsochatzis, E. A., Casazza, G., Nikolova, D., Volcek, E., & Gluud, C. N. (2016) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd001511.pub2 · Cited by 14

On Approximations to the t-Distribution

Dudewicz, E. J., & Dalal, S. R. (1972) · Journal of Quality Technology · doi:10.1080/00224065.1972.11980550 · Cited by 14

Significance Levels for the Kuder-Richardson Twenty: An Automated Sampling Experiment Approach

Payne, W. H., & Anderson, D. E. (1968) · Educational and Psychological Measurement · doi:10.1177/001316446802800103 · Cited by 14

Effects of adenosine deaminase inhibition on active uptake and metabolism of adenosine in astrocytes in primary cultures

Matz, H., & Hertz, L. (1990) · Brain Research · doi:10.1016/0006-8993(90)90592-y · Cited by 14

Variation in the yields of fruit trees in relation to the planning of future experiments

Parker, E. R., & Batchelor, L. D. (1932) · Hilgardia · doi:10.3733/hilg.v07n02p081 · Cited by 14

Inhibitory and stimulatory action of vasopressin on the secretion of corticotrophin in rats: Structure-activity study

van Dijk, A. A., Lodewijks, H. M. J. M., van Ree, J. M., & Greidanus, T. B. V. W. (1981) · Life Sciences · doi:10.1016/0024-3205(81)90198-3 · Cited by 14

The damage of the hepatic mixed functional oxygenase system by CCl4: Significance of incorporation of 14CCl4 metabolites in vivo

Fander, U., Haas, W., & Kröner, H. (1982) · Experimental and Molecular Pathology · doi:10.1016/0014-4800(82)90077-6 · Cited by 14

Automatic Detection and Assessment of Freezing of Gait Manifestations

Yang, P.-K., Filtjens, B., Ginis, P., Goris, M., Nieuwboer, A., Gilat, M., Slaets, P., & Vanrumste, B. (2024) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2024.3431208 · Cited by 15

Increasing Enzyme Mannose-6-Phosphate Levels but Not Miglustat Coadministration Enhances the Efficacy of Enzyme Replacement Therapy in Pompe Mice

Anding, A. L., Kinton, S., Baranowski, K., Brezzani, A., Busser, H. M. D., Dufault, M. R., Finn, P. F., Keefe, K., Tetrault, T., Li, Y., et al. (2023) · Journal of Pharmacology and Experimental Therapeutics · doi:10.1124/jpet.123.001593 · Cited by 13

Maximising the value of transmitted data from PSATs tracking marine fish: a case study on Atlantic bluefin tuna

Horton, T. W., Birch, S., Block, B. A., Hawkes, L. A., van der Kooij, J., Witt, M. J., & Righton, D. A. (2024) · Animal Biotelemetry · doi:10.1186/s40317-023-00356-9 · Cited by 14

Utilization of Internet-Based Survivorship Care Plans by Lung Cancer Survivors

Hill‐Kayser, C. E., Vachani, C. C., Hampshire, M. K., Jacobs, L. A., & Metz, J. M. (2009) · Clinical Lung Cancer · doi:10.3816/clc.2009.n.047 · Cited by 13

Role of DEAD-box RNA helicase genes in the growth of Yersinia pseudotuberculosis IP32953 under cold, pH, osmotic, ethanol and oxidative stresses

Jiang, X., Keto‐Timonen, R., Skurnik, M., & Korkeala, H. J. (2019) · PLoS ONE · doi:10.1371/journal.pone.0219422 · Cited by 13

On Post-selection Inference in A/B Testing

Deng, A., Li, Y., Lu, J., & Ramamurthy, V. (2021) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3447548.3467129 · Cited by 13

Cold Stress Activates the Expression of Genes of the Chloroplast Transcription Apparatus in Arabidopsis thaliana Plants

Bychkov, I. A., Kudryakova, N. V., Кузнецов, В. В., & Kusnetsov, V. V. (2020) · Doklady Biochemistry and Biophysics · doi:10.1134/s160767292005004x · Cited by 13

A Model of Scientific Data Reasoning

Masnick, A. M., & Morris, B. J. (2022) · Education Sciences · doi:10.3390/educsci12020071 · Cited by 13

Block-bootstrapping for noisy data

Mader, M., Mader, W., Sommerlade, L., Timmer, J., & Schelter, B. O. (2013) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2013.07.022 · Cited by 13

Experimental evaluation of a vehicle steering assist controller using a driving simulator

Chen, L., & Ulsoy, A. G. (2005) · Vehicle System Dynamics · doi:10.1080/00423110500268350 · Cited by 13

Theoretical Study on a Statistical Method for the Simple and Reliable Pre-Selection of Wheat Malt Types for Brewing Purposes Based on Generally Accepted Quality Characteristics

Titze, J., Faltermaier, A., Schnitzenbaumer, B., Gastl, M. I., Becker, T. M., Ilberg, V., & Arendt, E. K. (2013) · Journal of the American Society of Brewing Chemists · doi:10.1094/asbcj-2013-0407-01 · Cited by 13

Tardigrades of the Canopy: Argentine SpeciesMilnesium beataeRoszkowska, Ostrowska and Kaczmarek, 2015 (Eutardigrada, Milnesidae) Discovered in the Trees of Kansas, U.S.A.

Tibbs‐Cortes, L. E., Emanuels, A. F., & Miller, W. R. (2016) · Transactions of the Kansas Academy of Science · doi:10.1660/062.119.0207 · Cited by 13

Explorations in statistics: statistical facets of reproducibility

Curran‐Everett, D. (2016) · AJP Advances in Physiology Education · doi:10.1152/advan.00042.2016 · Cited by 14

Uncertainty estimation with a small number of measurements, part I: new insights on the t -interval method and its limitations

Huang, H. (2017) · Measurement Science and Technology · doi:10.1088/1361-6501/aa96c7 · Cited by 13

A Super Descriptor Tensor Decomposition for Dynamic Scene Recognition

Khokher, M. R., Bouzerdoum, A., & Phung, S. L. (2018) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2018.2825784 · Cited by 13

Anatomical Distribution of Diarrhetic Shellfish Toxins (DSTs) in the Japanese Scallop Patinopecten yessoensis and Individual Variability in Scallops and Mytilus edulis Mussels: Statistical Considerations

Matsushima, R., Uchida, H., Watanabe, R., Oikawa, H., Izumi, O., Kosaka, Y., Kanamori, M., Akamine, T., & Suzuki, T. (2018) · Toxins · doi:10.3390/toxins10100395 · Cited by 13

A Null Model for Pearson Coexpression Networks

Gobbi, A., & Jurman, G. (2015) · PLoS ONE · doi:10.1371/journal.pone.0128115 · Cited by 13

The Performance of Gene Expression Signature-Guided Drug–Disease Association in Different Categories of Drugs and Diseases

Qi, X., Shen, M., Fan, P., Guo, X., Wang, T., Feng, N., Zhang, M., Sweet, R. A., Kirisci, L., & Wang, L. (2020) · Molecules · doi:10.3390/molecules25122776 · Cited by 13

Improving Accuracy of an Artificial Neural Network Model to Predict Effort and Errors in Embedded Software Development Projects

Iwata, K., Nakashima, T., Anan, Y., & Ishii, N. (2010) · Studies in computational intelligence · doi:10.1007/978-3-642-13265-0_2 · Cited by 13

Algorithm 344: student's t -distribution [S14]

Levine, D. A. (1969) · Communications of the ACM · doi:10.1145/362835.362841 · Cited by 13

343. Studies of the Biological Value of the Proteins (Nitrogen) of Dried Skim Milk: Value As An Addition to Bread; Tests With Young and Olderrats; Effects of Storage

Henry, K. M., & Rowland, S. J. (1946) · Journal of Dairy Research · doi:10.1017/s0022029900004842 · Cited by 13

Vorgehensweisen in der deutschsprachigen psychologischen Forschung

Hager, W. (2005) · Psychologische Rundschau · doi:10.1026/0033-3042.56.3.191 · Cited by 13

Economic Statistics and Econometrics

Darnell, A. C. (1984) · Elsevier eBooks · doi:10.1016/b978-0-408-11430-1.50012-6 · Cited by 13

Comparative study of the safety and efficacy of liquid and dry monopolar electrocoagulation in experimental canine bleeding ulcers using computerized energy monitoring

Swain, C. P., Mills, T. N., Dark, J. M., Lewin, M. R., Bown, S. G., Northfield, T. C., O'Sullivan, J. P., & Salmon, P. R. (1984) · Gastroenterology · doi:10.1016/0016-5085(84)90594-8 · Cited by 13

Who Gives Direction to Statistical Testing? Best Practice Meets Mathematically Correct TestsPreprint

Schlag, K. H. (2015) · SSRN Electronic Journal · doi:10.2139/ssrn.2660977 · Cited by 13

Resilience Factors of Ukrainian Micro, Small, and Medium-Sized Business

Длігач, А. О., & Stavytskyy, A. V. (2024) · Economies · doi:10.3390/economies12120319 · Cited by 12

Amplified potential for vegetation stress under climate-change-induced intensifying compound extreme events in the Greater Mediterranean Region

Olschewski, P., Dieng, D., Moutahir, H., Böker, B., Haas, E., Kunstmann, H. G., & Laux, P. (2024) · Natural hazards and earth system sciences · doi:10.5194/nhess-24-1099-2024 · Cited by 15

Perception of the Vegetation Elements of Urban Green Spaces with a Focus on Flower Beds

Poje, M., Vukelić, A., Židovec, V., Prebeg, T., & Kušen, M. (2024) · Plants · doi:10.3390/plants13172485 · Cited by 13

Pectobacterium parmentieri SCC 3193 Mutants with Altered Synthesis of Cell Surface Polysaccharides Are Resistant to N4-Like Lytic Bacteriophage ϕA38 (vB_Ppp_A38) but Express Decreased Virulence in Potato (Solanum tuberosum L.) Plants

Bartnik, P., Jafra, S., Narajczyk, M., Czaplewska, P., & Czajkowski, R. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22147346 · Cited by 12

On the Probable Error of Mean-Square Contingency

BLAKEMAN, J., & Pearson, K. (1906) · Biometrika · doi:10.2307/2331660 · Cited by 2

ON THE PROBABLE ERROR OF BISERIAL

Pearson, K. (1917) · Biometrika · doi:10.1093/biomet/11.4.292

The Law of Error.

E., W. P., Edgeworth, F. Y., & Charlier, C. V. L. (1906) · Biometrika · doi:10.2307/2331663 · Cited by 2

TABLES FOR FACILITATING THE COMPUTATION OF PROBABLE ERRORS

GIBSON, W. (1906) · Biometrika · doi:10.1093/biomet/4.4.385 · Cited by 2

On Certain Points Concerning the Probable Error of the Standard Deviation

Pearl, R. (1908) · Biometrika · doi:10.2307/2331564 · Cited by 1