A concordance correlation coefficient to evaluate reproducibility.
Abstract
A new reproducibility index is developed and studied. This index is the correlation between the two readings that fall on the 45 degree line through the origin. It is simple to use and possesses desirable properties. The statistical properties of this estimate can be satisfactorily evaluated using an inverse hyperbolic tangent transformation. A Monte Carlo experiment with 5,000 runs was performed to confirm the estimate's validity. An application using actual data is given.
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All parameters used for the proposition and cross-validation of the model confirmed their validity for the studied population.
“and all parameters used for the proposition and cross-validation of the model confirmed their validity for the studied population (15, 37–39, 57)”
From Development and Cross-Validation of a Predictive Equation for Fat-Free Mass in Brazilian Adolescents by Bioelectrical Impedance (2022) · cites this paper as [38]
Explicit maximisation of the concordance correlation coefficient (rho_c) in the model improves emotion prediction compared to optimising the mean square error objective.
“Furthermore, we suggest using explicit maximisation of the concordance correlation coefficient ( ρ c ) [9] in our model and show that this improves performance in terms of emotion prediction compared to optimising the mean square error objective, which is traditionally used.”
From End-to-End Multimodal Emotion Recognition using Deep Neural Networks (2017) · cites this paper as [9]
Cohen's quadratically weighted kappa coincides with Lin's bivariate concordance correlation coefficient.
“showing that Cohen's quadratically weighted kappa coincides with Lin's bivariate concordance correlation coefficient (Lin, 1989).”
From Quadratically Weighted Agreement Coefficients: Interpretations and Connections (2026) · cites this paper as Lin, 1989
If available, test-retest data are extremely helpful, as they can help prioritize features on the basis of their reproducibility.
“If available, test-retest data are also extremely helpful, as they can help prioritize features on the basis of their reproducibility (51,52).”
From Radiomics: Images Are More than Pictures, They Are Data (2016) · cites this paper as [51]
Cites
Bootstrap methods: another look at the jackknife
Efron, B. (1979) · The Annals of Statistics · doi:10.1214/aos/1176344552 · Cited by 17,602 · see citing works
Approximation Theorems of Mathematical Statistics
Serfling, R. J. (1980) · Wiley series in probability and statistics · doi:10.1002/9780470316481 · Cited by 5,959 · see citing works
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Radiomics: Images Are More than Pictures, They Are Data
Gillies, R. J., Kinahan, P. E., & Hricak, H. (2016) · Radiology · doi:10.1148/radiol.2015151169 · Cited by 8,421 · see citing works
Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project
Conroy, R. (2003) · European Heart Journal · doi:10.1016/s0195-668x(03)00114-3 · Cited by 5,290 · see citing works
Content Analysis in Mass Communication: Assessment and Reporting of Intercoder Reliability
Lombard, M., Snyder-Duch, J., & Bracken, C. C. (2002) · Human Communication Research · doi:10.1111/j.1468-2958.2002.tb00826.x · Cited by 3,068 · see citing works
Within-subject template estimation for unbiased longitudinal image analysis
Reuter, M., Schmansky, N. J., Rosas, H. D., & Fischl, B. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.02.084 · Cited by 2,356 · see citing works
Cognitive and Behavioral Outcomes of School-Aged Children Who Were Born Preterm: A Meta-analysis
Bhutta, A. T., Cleves, M. A., Casey, P. H., Cradock, M. M., & Anand, K. J. S. (2002) · JAMA · doi:10.1001/jama.288.6.728 · Cited by 2,392 · see citing works
Magnetic resonance fingerprinting
Ma, D., Gulani, V., Seiberlich, N., Liu, K., Sunshine, J. L., Duerk, J. L., & Griswold, M. A. (2013) · Nature · doi:10.1038/nature11971 · Cited by 1,577 · see citing works
Biomarkers of mitochondrial content in skeletal muscle of healthy young human subjects
Larsen, S., Nielsen, J., Hansen, C. N., Nielsen, L. B., Wibrand, F., Stride, N., Schroder, H. D., Boushel, R., Helge, J. W., Dela, F., et al. (2012) · The Journal of Physiology · doi:10.1113/jphysiol.2012.230185 · Cited by 1,180 · see citing works
Beyond kappa: a review of interrater agreement measures
Banerjee, M., Capozzoli, M., McSweeney, L., & Sinha, D. (1999) · Canadian Journal of Statistics · doi:10.2307/3315487 · Cited by 976 · see citing works
Adieu features? End-to-end speech emotion recognition using a deep convolutional recurrent network
Trigeorgis, G., Ringeval, F., Brueckner, R., Marchi, E., Nicolaou, M. A., Schuller, B., & Zafeiriou, S. (2016) · 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) · doi:10.1109/icassp.2016.7472669 · Cited by 904 · see citing works
End-to-End Multimodal Emotion Recognition using Deep Neural Networks
Tzirakis, P., Trigeorgis, G., Nicolaou, M. A., Schuller, B., & Zafeiriou, S. (2017) · arXiv · doi:10.48550/arxiv.1704.08619 · Cited by 752 · see citing works
Violating the normality assumption may be the lesser of two evils
Knief, U., & Forstmeier, W. (2021) · Behavior Research Methods · doi:10.3758/s13428-021-01587-5 · Cited by 654 · see citing works
“We assessed the deviation of observed from expected -log10(P-value) at an expected value of 3 (P = 10−3) and 4 (P = 10−4) and by estimating the scale shift parameter v = σobserved / σexpected (Lin 1989), where σ is the variance in -log10(P-value).”
BackgroundHow accurate is pulse rate variability as an estimate of heart rate variability?
Schäfer, A., & Vagedes, J. (2013) · International Journal of Cardiology · doi:10.1016/j.ijcard.2012.03.119 · Cited by 661 · see citing works
Nishino, M., Giobbie-Hurder, A., Gargano, M., Suda, M., Ramaiya, N. H., & Hodi, F. S. (2013) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-13-0895 · Cited by 522 · see citing works
Development and validation of a short version of the Kansas City Cardiomyopathy Questionnaire
Spertus, J. A., & Jones, P. G. (2015) · Circulation Cardiovascular Quality and Outcomes · doi:10.1161/circoutcomes.115.001958 · Cited by 491 · see citing works
Decrease in cortisol reverses human hippocampal atrophy following treatment of Cushing’s disease
Starkman, M. N., Giordani, B., Gebarski, S. S., Berent, S., Schork, M. A., & Schteingart, D. E. (1999) · Biological Psychiatry · doi:10.1016/s0006-3223(99)00203-6 · Cited by 455 · see citing works
McAlinden, C., Khadka, J., & Pesudovs, K. (2011) · Ophthalmic and Physiological Optics · doi:10.1111/j.1475-1313.2011.00851.x · Cited by 436 · see citing works
Ringeval, F., Schuller, B., Valstar, M., Cummins, N., Cowie, R., Tavabi, L., Schmitt, M., Alisamir, S., Amiriparian, S., Messner, E.-M., et al. (2019) · Proceedings of the 9th International on Audio/Visual Emotion Challenge and Workshop · doi:10.1145/3347320.3357688 · Cited by 409 · see citing works
Data exploration, quality control and testing in single-cell qPCR-based gene expression experiments
McDavid, A., Finak, G., Chattopadyay, P. K., Dominguez, M., Lamoreaux, L., Ma, S. S., Roederer, M., & Gottardo, R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts714 · Cited by 395 · see citing works
Evans-Lacko, S., Rose, D., Little, K., Flach, C., Rhydderch, D., Henderson, C., & Thornicroft, G. (2011) · Epidemiology and Psychiatric Sciences · doi:10.1017/s2045796011000308 · Cited by 363 · see citing works
Schaffarczyk, M., Rogers, B., Reer, R., & Gronwald, T. (2022) · Sensors · doi:10.3390/s22176536 · Cited by 349 · see citing works
Achamrah, N., Colange, G., Delay, J., Rimbert, A., Folope, V., Petit, A., Grigioni, S., Déchelotte, P., & Coëffier, M. (2018) · PLoS ONE · doi:10.1371/journal.pone.0200465 · Cited by 337 · see citing works
Variable Accuracy of Wearable Heart Rate Monitors during Aerobic Exercise
GILLINOV, S., ETIWY, M., WANG, R., BLACKBURN, G., PHELAN, D., GILLINOV, A. M., HOUGHTALING, P., JAVADIKASGARI, H., & DESAI, M. Y. (2017) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0000000000001284 · Cited by 345 · see citing works
Clement, S., Brohan, E., Jeffery, D., Henderson, C., Hatch, S. L., & Thornicroft, G. (2012) · BMC Psychiatry · doi:10.1186/1471-244x-12-36 · Cited by 314 · see citing works
Doshi, J., Erus, G., Ou, Y., Resnick, S. M., Gur, R. C., Gur, R. E., Satterthwaite, T. D., Furth, S., & Davatzikos, C. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.11.073 · Cited by 309 · see citing works
“We calculated Pearson's correlation coefficient (r), concordance correlation coefficient (ccc) (Lin, 1989) and mean absolute error (MAE) as quantitative metrics of prediction accuracy.”
Cell type prioritization in single-cell data
Skinnider, M. A., Squair, J. W., Kathe, C., Anderson, M. A., Gautier, M., Matson, K. J. E., Milano, M., Hutson, T. H., Barraud, Q., Phillips, A. A., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-020-0605-1 · Cited by 274 · see citing works
Grove, O., Berglund, A. E., Schabath, M. B., Aerts, H. J. W. L., Dekker, A., Wang, H., Velazquez, E. R., Lambin, P., Gu, Y., Balagurunathan, Y., et al. (2015) · PLOS ONE · doi:10.1371/journal.pone.0118261 · Cited by 263 · see citing works
Baker, L. B., Model, J. B., Barnes, K. A., Anderson, M. L., Lee, S. P., Lee, K. A., Brown, S. D., Reimel, A. J., Roberts, T. J., Nuccio, R. P., et al. (2020) · Science Advances · doi:10.1126/sciadv.abe3929 · Cited by 243 · see citing works
Development and psychometric evaluation of the Discrimination and Stigma Scale (DISC)
Brohan, E., Clement, S., Rose, D., Sartorius, N., Slade, M., & Thornicroft, G. (2013) · Psychiatry Research · doi:10.1016/j.psychres.2013.03.007 · Cited by 196 · see citing works
Multibatch TMT reveals false positives, batch effects and missing values
Brenes, A., Hukelmann, J., Bensaddek, D., & Lamond, A. I. (2019) · Molecular & Cellular Proteomics · doi:10.1074/mcp.ra119.001472 · Cited by 196 · see citing works
Prediction of asynchronous dimensional emotion ratings from audiovisual and physiological data
Ringeval, F., Eyben, F., Kroupi, E., Yuce, A., Thiran, J.-P., Ebrahimi, T., Lalanne, D., & Schuller, B. (2015) · Pattern Recognition Letters · doi:10.1016/j.patrec.2014.11.007 · Cited by 202 · see citing works
Functional connectivity of visual cortex in the blind follows retinotopic organization principles
Striem-Amit, E., Ovadia-Caro, S., Caramazza, A., Margulies, D. S., Villringer, A., & Amedi, A. (2015) · Brain · doi:10.1093/brain/awv083 · Cited by 194 · see citing works
Carbonation of brine impacted fractionated coal fly ash: Implications for CO2 sequestration
Nyambura, M. G., Mugera, G. W., Felicia, P. L., & Gathura, N. P. (2011) · Journal of Environmental Management · doi:10.1016/j.jenvman.2010.10.008 · Cited by 191 · see citing works
Mehta, S., Bastero‐Caballero, R. F., Sun, Y., Zhu, R., Murphy, D. K., Hardas, B., & Koch, G. (2018) · Statistics in Medicine · doi:10.1002/sim.7679 · Cited by 193 · see citing works
Moradmand, H., Aghamiri, S. M. R., & Ghaderi, R. (2020) · Journal of Applied Clinical Medical Physics · doi:10.1002/acm2.12795 · Cited by 173 · see citing works
Anderson, L. J., Erceg, D. N., & Schroeder, E. T. (2012) · Nutrition Research · doi:10.1016/j.nutres.2012.05.009 · Cited by 167 · see citing works
Saliva collection method affects predictability of serum cortisol.
Poll, E.-M., Kreitschmann-Andermahr, I., Langejuergen, Y., Stanzel, S., Gilsbach, J. M., Gressner, A., & Yagmur, E. (2007) · Clinica Chimica Acta · doi:10.1016/j.cca.2007.03.009 · Cited by 162 · see citing works
The Longitudinal Outcome of Fibromyalgia: A Study of 1555 Patients
WALITT, B., FITZCHARLES, M.-A., HASSETT, A. L., KATZ, R. S., HÄUSER, W., & WOLFE, F. (2011) · The Journal of Rheumatology · doi:10.3899/jrheum.110026 · Cited by 154 · see citing works
PastureBase Ireland: a grassland decision support system and national database
Hanrahan, L., Geoghegan, A., O'Donovan, M., Griffith, V., Ruelle, E., Wallace, M., & Shalloo, L. (2017) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2017.01.029 · Cited by 151 · see citing works
A comparison of two methods of collecting economic data in primary care
Patel, A., Rendu, A., Moran, P., Leese, M., Mann, A., & Knapp, M. (2005) · Family Practice · doi:10.1093/fampra/cmi027 · Cited by 149 · see citing works
Ontogeny and phylogeny of language
Yang, C. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1216803110 · Cited by 142 · see citing works
Shapes of the Trajectories of 5 Major Biomarkers of Alzheimer Disease
Jack, C. R., Vemuri, P., Wiste, H. J., Weigand, S. D., Lesnick, T. G., Lowe, V., Kantarci, K., Bernstein, M. A., Senjem, M. L., Gunter, J. L., et al. (2012) · Archives of Neurology · doi:10.1001/archneurol.2011.3405 · Cited by 145 · see citing works
Accuracy of wearable heart rate monitors in cardiac rehabilitation
Etiwy, M., Akhrass, Z., Gillinov, L., Alashi, A., Wang, R., Blackburn, G., Gillinov, S. M., Phelan, D., Gillinov, A. M., Houghtaling, P. L., et al. (2019) · Cardiovascular Diagnosis and Therapy · doi:10.21037/cdt.2019.04.08 · Cited by 143 · see citing works
Avramenko, R. W., Redman, E. M., Melville, L., Bartley, Y., Wit, J., Queiroz, C., Bartley, D. J., & Gilleard, J. S. (2019) · International Journal for Parasitology · doi:10.1016/j.ijpara.2018.10.005 · Cited by 123 · see citing works
Effects of transport and lairage time on some blood constituents of Friesian-cross steers in Chile
Tadich, N., Gallo, C., Bustamante, H., Schwerter, M., & van Schaik, G. (2005) · Livestock Production Science · doi:10.1016/j.livprodsci.2004.10.004 · Cited by 142 · see citing works
Artificial intelligence in pancreatic cancer
Huang, B., Huang, H., Zhang, S., Zhang, D., Shi, Q., Liu, J., & Guo, J. (2022) · Theranostics · doi:10.7150/thno.77949 · Cited by 142 · see citing works
“The repeatability of radiomics features can be assessed using consistency correlation coefficients (CCCs) [272].”
MethodStrand, S., Lutter, W., Strasburger, J. F., Shah, V., Baffa, O., & Wakai, R. T. (2019) · Journal of the American Heart Association · doi:10.1161/jaha.119.013436 · Cited by 136 · see citing works
“Concordance between the OPM-CS and SQUID-MSR measurements was evaluated by computing the concordance correlation coefficient.(11) Coefficients >0.”
MethodAccuracy of commercially available heart rate monitors in athletes: a prospective study
Pasadyn, S. R., Soudan, M., Gillinov, M., Houghtaling, P., Phelan, D., Gillinov, N., Bittel, B., & Desai, M. Y. (2019) · Cardiovascular Diagnosis and Therapy · doi:10.21037/cdt.2019.06.05 · Cited by 135 · see citing works
Toosizadeh, N., Mohler, J., Lei, H., Parvaneh, S., Sherman, S., & Najafi, B. (2015) · PLOS ONE · doi:10.1371/journal.pone.0124763 · Cited by 117 · see citing works
Alterations in mucosal immunity identified in the colon of patients with irritable bowel syndrome
Aerssens, J., Camilleri, M., Talloen, W., Thielemans, L., Göhlmann, H. W. H., Van den Wyngaert, I., Thielemans, T., De Hoogt, R., Andrews, C. N., Bharucha, A. E., et al. (2008) · Clinical Gastroenterology and Hepatology · doi:10.1016/j.cgh.2007.11.012 · Cited by 124 · see citing works
Gunga, H.-C., Werner, A., Stahn, A., Steinach, M., Schlabs, T., Koralewski, E., Kunz, D., Belavý, D. L., Felsenberg, D., Sattler, F., et al. (2009) · Respiratory Physiology & Neurobiology · doi:10.1016/j.resp.2009.04.005 · Cited by 122 · see citing works
Nielsen, J., Holmberg, H., Schrøder, H. D., Saltin, B., & Ørtenblad, N. (2011) · The Journal of Physiology · doi:10.1113/jphysiol.2010.204487 · Cited by 122 · see citing works
The OMG-Emotion Behavior Dataset
Barros, P., Churamani, N., Lakomkin, E., Siqueira, H., Sutherland, A., & Wermter, S. (2018) · 2018 International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2018.8489099 · Cited by 121 · see citing works
The Concordance Correlation Coefficient for Repeated Measures Estimated by Variance Components
Carrasco, J. L., King, T. S., & Chinchilli, V. M. (2009) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543400802527890 · Cited by 111 · see citing works
Vinikoor, L. C., Messer, L. C., Laraia, B. A., & Kaufman, J. S. (2010) · Paediatric and Perinatal Epidemiology · doi:10.1111/j.1365-3016.2009.01087.x · Cited by 109 · see citing works
Bane, O., Hectors, S. J., Wagner, M., Arlinghaus, L. L., Aryal, M. P., Cao, Y., Chenevert, T. L., Fennessy, F., Huang, W., Hylton, N. M., et al. (2018) · Magnetic Resonance in Medicine · doi:10.1002/mrm.26903 · Cited by 109 · see citing works
Matias, C. N., Santos, D. A., Júdice, P. B., Magalhães, J. P., Minderico, C. S., Fields, D. A., Lukaski, H. C., Sardinha, L. B., & Silva, A. M. (2016) · Clinical Nutrition · doi:10.1016/j.clnu.2015.03.013 · Cited by 108 · see citing works
Lu, L., Dercle, L., Zhao, B., & Schwartz, L. H. (2021) · Nature Communications · doi:10.1038/s41467-021-26990-6 · Cited by 104 · see citing works
Nishino, M., Gargano, M., Suda, M., Ramaiya, N. H., & Hodi, F. S. (2014) · Journal for ImmunoTherapy of Cancer · doi:10.1186/2051-1426-2-17 · Cited by 95 · see citing works
Motivational interviewing: a pilot test of active ingredients and mechanisms of change
Morgenstern, J., Kuerbis, A., Amrhein, P., Hail, L., Lynch, K., & McKay, J. R. (2012) · Psychology of Addictive Behaviors · doi:10.1037/a0029674 · Cited by 93 · see citing works
Shifren, J. L., Desindes, S., McIlwain, M., Doros, G., & Mazer, N. A. (2007) · Menopause · doi:10.1097/gme.0b013e31803867a · Cited by 89 · see citing works
Ethnic differences in associations between blood pressure and stroke in south Asian and European men
Eastwood, S. V., Tillin, T., Chaturvedi, N., & Hughes, A. D. (2015) · Hypertension · doi:10.1161/hypertensionaha.115.05672 · Cited by 82 · see citing works
Prediction of Fatness by Standing 8‐Electrode Bioimpedance: A Multiethnic Adolescent Population
Sluyter, J. D., Schaaf, D., Scragg, R. K. R., & Plank, L. D. (2010) · Obesity · doi:10.1038/oby.2009.166 · Cited by 85 · see citing works
Markerless Pancreatic Tumor Target Localization Enabled By Deep Learning
Zhao, W., Shen, L., Han, B., Yang, Y., Cheng, K., Toesca, D. A. S., Koong, A. C., Chang, D. T., & Xing, L. (2019) · International Journal of Radiation Oncology*Biology*Physics · doi:10.1016/j.ijrobp.2019.05.071 · Cited by 88 · see citing works
Sadhu, A. R., Serrano, I. A., Xu, J., Nisar, T., Lucier, J., Pandya, A. R., & Patham, B. (2020) · Journal of Diabetes Science and Technology · doi:10.1177/1932296820964264 · Cited by 84 · see citing works
Hanggi, M. P., Teuscher, U. M., Roos, M., & Peltomaki, T. A. (2008) · The European Journal of Orthodontics · doi:10.1093/ejo/cjn055 · Cited by 85 · see citing works
Sun, L., Lian, Z., Tao, J., Liu, B., & Niu, M. (2020) · Proceedings of the 1st International on Multimodal Sentiment Analysis in Real-life Media Challenge and Workshop · doi:10.1145/3423327.3423672 · Cited by 81 · see citing works
Zakeri, I., Adolph, A. L., Puyau, M. R., Vohra, F. A., & Butte, N. F. (2008) · Journal of Applied Physiology · doi:10.1152/japplphysiol.01163.2007 · Cited by 80 · see citing works
Parvaneh, S., Mohler, J., Toosizadeh, N., Grewal, G. S., & Najafi, B. (2017) · Gerontology · doi:10.1159/000460292 · Cited by 67 · see citing works
Berg, J.-L., Durant, J., Léger, G. C., Cummings, J. L., Nasreddine, Z., & Miller, J. B. (2018) · Journal of Alzheimer’s Disease · doi:10.3233/jad-170896 · Cited by 72 · see citing works
A new approach to the assessment of anaerobic metabolism: measurement of lactate in saliva.
Segura, R., Javierre, C., Ventura, J. L., Lizarraga, M. A., Campos, B., & Garrido, E. (1996) · British Journal of Sports Medicine · doi:10.1136/bjsm.30.4.305 · Cited by 71 · see citing works
Scott, E. P., Sorrell, A., & Benitez, A. (2019) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617719000614 · Cited by 69 · see citing works
Prioritization of cell types responsive to biological perturbations in single-cell data with Augur
Squair, J. W., Skinnider, M. A., Gautier, M., Foster, L. J., & Courtine, G. (2021) · Nature Protocols · doi:10.1038/s41596-021-00561-x · Cited by 61 · see citing works
Rush, E. C., Chandu, V, & Plank, L. D. (2006) · International Journal of Obesity · doi:10.1038/sj.ijo.0803230 · Cited by 65 · see citing works
Rickman, D. S., Chen, Y.-B., Banerjee, S., Pan, Y., Yu, J., Vuong, T., Perner, S., Lafargue, C. J., Mertz, K. D., Setlur, S. R., et al. (2010) · Neoplasia · doi:10.1593/neo.10866 · Cited by 62 · see citing works
Sifakakis, I., Papaioannou, W., Papadimitriou, A., Kloukos, D., Papageorgiou, S. N., & Eliades, T. (2018) · Progress in Orthodontics · doi:10.1186/s40510-018-0230-4 · Cited by 59 · see citing works
Matias, C. N., Campa, F., Santos, D. A., Lukaski, H., Sardinha, L. B., & Silva, A. M. (2021) · International Journal of Sports Medicine · doi:10.1055/a-1179-6236 · Cited by 54 · see citing works
Silva, A. M., Fields, D. A., & Sardinha, L. B. (2013) · Journal of Obesity · doi:10.1155/2013/148696 · Cited by 52 · see citing works
Vetrovsky, T., Siranec, M., Marencakova, J., Tufano, J. J., Capek, V., Bunc, V., & Belohlavek, J. (2019) · PLOS ONE · doi:10.1371/journal.pone.0222569 · Cited by 53 · see citing works
Barteit, S., Boudo, V., Ouedraogo, A., Zabré, P., Ouremi, L., Sié, A., Munga, S., Obor, D., Kwaro, D., Huhn, S., et al. (2021) · PLOS ONE · doi:10.1371/journal.pone.0257170 · Cited by 51 · see citing works
Patterson, E. A., Whelan, M. P., & Worth, A. P. (2021) · Computational Toxicology · doi:10.1016/j.comtox.2020.100144 · Cited by 47 · see citing works
Peer Review versus Bibliometrics: Which Method Better Predicts the Scholarly Impact of Publications?
Abramo, G., D’Angelo, C. A., & Reale, E. (2019) · Scientometrics · doi:10.1007/s11192-019-03184-y · Cited by 50 · see citing works
Validity of Bioelectrical Impedance Analysis to Estimation Fat-Free Mass in the Army Cadets
Langer, R., Borges, J., Pascoa, M., Cirolini, V., Guerra-Júnior, G., & Gonçalves, E. (2016) · Nutrients · doi:10.3390/nu8030121 · Cited by 44 · see citing works
Darwich, A. S., Margolskee, A., Pepin, X., Aarons, L., Galetin, A., Rostami-Hodjegan, A., Carlert, S., Hammarberg, M., Hilgendorf, C., Johansson, P., et al. (2017) · European Journal of Pharmaceutical Sciences · doi:10.1016/j.ejps.2016.09.037 · Cited by 45 · see citing works
Guite, J. W., Kim, S., Chen, C.-P., Sherker, J. L., Sherry, D. D., Rose, J. B., & Hwang, W.-T. (2014) · The Clinical Journal of Pain · doi:10.1097/ajp.0b013e31828518e9 · Cited by 41 · see citing works
Panda, A., Korfiatis, P., Suman, G., Garg, S. K., Polley, E. C., Singh, D. P., Chari, S. T., & Goenka, A. H. (2021) · Medical Physics · doi:10.1002/mp.14782 · Cited by 41 · see citing works
Bridge, P., Pocock, N. A., Nguyen, T., Munns, C., Cowell, C. T., Forwood, N., & Thompson, M. W. (2011) · Journal of Clinical Densitometry · doi:10.1016/j.jocd.2011.04.005 · Cited by 40 · see citing works
Sardinha, L. B., Correia, I. R., Magalhães, J. P., Júdice, P. B., Silva, A. M., & Hetherington-Rauth, M. (2020) · European Journal of Clinical Nutrition · doi:10.1038/s41430-020-0666-8 · Cited by 38 · see citing works
Laporte, C., Vaillant-Roussel, H., Pereira, B., Blanc, O., Eschalier, B., Kinouani, S., Brousse, G., Llorca, P.-M., & Vorilhon, P. (2017) · The Annals of Family Medicine · doi:10.1370/afm.2003 · Cited by 36 · see citing works
Multimodal Emotion Recognition and Sentiment Analysis via Attention Enhanced Recurrent Model
Sun, L., Xu, M., Lian, Z., Liu, B., Tao, J., Wang, M., & Cheng, Y. (2021) · Proceedings of the 2nd on Multimodal Sentiment Analysis Challenge · doi:10.1145/3475957.3484456 · Cited by 36 · see citing works
Sarkar, R. (2014) · Indian Journal of Clinical Biochemistry · doi:10.1007/s12291-013-0339-7 · Cited by 34 · see citing works
Campa, F., Matias, C. N., Moro, T., Cerullo, G., Casolo, A., Teixeira, F. J., & Paoli, A. (2023) · Nutrients · doi:10.3390/nu15020278 · Cited by 33 · see citing works
Asymptotic variability of (multilevel) multirater kappa coefficients
Vanbelle, S. (2019) · Statistical Methods in Medical Research · doi:10.1177/0962280218794733 · Cited by 33 · see citing works
Lanzarini, L., Larizza, D., Prete, G., Calcaterra, V., Meloni, G., Sammarchi, L., & Klersy, C. (2007) · Journal of Cardiovascular Medicine · doi:10.2459/01.jcm.0000269716.33435.d3 · Cited by 30 · see citing works
Validation of the Fitbit One® for physical activity measurement at an upper torso attachment site
Diaz, K. M., Krupka, D. J., Chang, M. J., Shaffer, J. A., Ma, Y., Goldsmith, J., Schwartz, J. E., & Davidson, K. W. (2016) · BMC Research Notes · doi:10.1186/s13104-016-2020-8 · Cited by 29 · see citing works
The accuracy of a disposable noninvasive core thermometer
Kimberger, O., Saager, L., Egan, C., Sanchez, I. P., Dizili, S., Koch, J., & Kurz, A. (2013) · Canadian Journal of Anesthesia/Journal canadien d'anesthésie · doi:10.1007/s12630-013-0047-z · Cited by 30 · see citing works
Luke, A., Bovet, P., Forrester, T. E., Lambert, E. V., Plange-Rhule, J., Dugas, L. R., Durazo-Arvizu, R. A., Kroff, J., Richie, W. N., & Schoeller, D. A. (2013) · European Journal of Clinical Nutrition · doi:10.1038/ejcn.2013.123 · Cited by 29 · see citing works
“Three parameters were computed, the coefficient of determination (R2), the mean squared error (MSE), and the concordance correlation coefficient (23).”
MethodKoury, J. C., Ribeiro, M. A., Massarani, F. A., Vieira, F., & Marini, E. (2019) · Nutrition · doi:10.1016/j.nut.2018.09.029 · Cited by 25 · see citing works
Mielke, G. I., de Almeida Mendes, M., Ekelund, U., Rowlands, A. V., Reichert, F. F., & Crochemore‐Silva, I. (2023) · Scandinavian Journal of Medicine & Science in Sports · doi:10.1111/sms.14416 · Cited by 26 · see citing works
Temporal and spatial dispersion of human body temperature during deep hypothermia
Opatz, O., Trippel, T., Lochner, A., Werner, A., Stahn, A., Steinach, M., Lenk, J., Kuppe, H., & Gunga, H. C. (2013) · British Journal of Anaesthesia · doi:10.1093/bja/aet217 · Cited by 22 · see citing works
“Our similarities are different” The relationship between alexithymia and depression
Kieraité, M., Bättig, J. J., Novoselac, A., Noboa, V., Seifritz, E., Rufer, M., Egger, S. T., & Weidt, S. (2024) · Psychiatry Research · doi:10.1016/j.psychres.2024.116099 · Cited by 19 · see citing works
- Authors
- Lin, L. I.-K.
- Affiliations
- Baxter (United States) (US)
- Corresponding author
- Lin, Lawrence I-Kuei
- Venue
- Biometrics
- Publisher
- JSTOR
- Published
- 1989-03
- Volume
- 45
- Issue
- 1
- Pages
- 255
- ISSN
- 0006-341X (ISSN-L)
- OpenAlex
- W2313339984
- Cited by
- 8,785
- References
- 2
- Citations by year
- 2026: 587 · 2025: 558 · 2024: 561 · 2023: 564 · 2022: 628 · 2021: 626 · 2020: 586 · 2019: 539 · 2018: 467 · 2017: 414 · 2016: 405 · 2015: 384 · 2014: 337 · 2013: 280 · 2012: 277
- FWCI
- 8.15
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biometrics (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Reliability and Agreement in Measurement
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Multidisciplinary Science and Engineering Research
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Keywords
- concordance correlation coefficient, reproducibility, measurement error, reproducibility index
- MeSH terms
- Analysis of Variance, Computer Simulation, Monte Carlo Method, Probability, Reproducibility of Results
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.
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