Applied Logistic Regression

Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence

Singer, J. D., & Willett, J. B. (2003) · doi:10.1093/acprof:oso/9780195152968.001.0001 · Cited by 10,647

The prevalence and correlates of eating disorders in the National Comorbidity Survey Replication

Hudson, J. I., Hiripi, E., Pope, H. G., & Kessler, R. C. (2007) · Biological Psychiatry · doi:10.1016/j.biopsych.2006.03.040 · Cited by 4,973

Purposeful selection of variables in logistic regression

Bursac, Z., Gauss, C. H., Williams, D. K., & Hosmer, D. W. (2008) · Source Code for Biology and Medicine · doi:10.1186/1751-0473-3-17 · Cited by 4,035

AUC: A misleading measure of the performance of predictive distribution models

Lobo, J. M., Jiménez‐Valverde, A., & Real, R. (2008) · Global Ecology and Biogeography · doi:10.1111/j.1466-8238.2007.00358.x · Cited by 3,499

The Fatty Liver Index: a simple and accurate predictor of hepatic steatosis in the general population

Bedogni, G., Bellentani, S., Miglioli, L., Masutti, F., Passalacqua, M., Castiglione, A., & Tiribelli, C. (2006) · BMC Gastroenterology · doi:10.1186/1471-230x-6-33 · Cited by 3,146

Cancer Cachexia in the Age of Obesity: Skeletal Muscle Depletion Is a Powerful Prognostic Factor, Independent of Body Mass Index

Martin, L., Birdsell, L., Macdonald, N., Reiman, T., Clandinin, M. T., McCargar, L. J., Murphy, R. A., Ghosh, S., Sawyer, M. B., & Baracos, V. E. (2013) · Journal of Clinical Oncology · doi:10.1200/jco.2012.45.2722 · Cited by 2,761

Revised diagnostic criteria for neuromyelitis optica

Wingerchuk, D. M., Lennon, V. A., Pittock, S. J., Lucchinetti, C. F., & Weinshenker, B. G. (2006) · Neurology · doi:10.1212/01.wnl.0000216139.44259.74 · Cited by 2,568

Generalized linear and generalized additive models in studies of species distributions: setting the scene

Guisan, A., Edwards, T. C., & Hastie, T. (2002) · Ecological Modelling · doi:10.1016/s0304-3800(02)00204-1 · Cited by 2,356

General and abdominal adiposity and risk of death in Europe

Pischon, T., Boeing, H., Hoffmann, K., Bergmann, M., Schulze, M. B., Overvad, K., van der Schouw, Y. T., Spencer, E., Moons, K. G. M., Tjønneland, A., et al. (2008) · New England Journal of Medicine · doi:10.1056/nejmoa0801891 · Cited by 2,155

The Smartphone addiction scale: development and validation of a short version for adolescents

Kwon, M., Kim, D.-J., Cho, H., & Yang, S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0083558 · Cited by 2,177

New ICD-10 version of the Charlson comorbidity index predicted in-hospital mortality

Sundararajan, V., Henderson, T., Perry, C., Muggivan, A., Quan, H., & Ghali, W. A. (2004) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2004.03.012 · Cited by 2,439

Logistic regression and Artificial Neural Network Classification models: A methodology review

Dreiseitl, S., & Ohno-Machado, L. (2002) · Journal of Biomedical Informatics · doi:10.1016/s1532-0464(03)00034-0 · Cited by 2,177

How Big is a Big Odds Ratio? Interpreting the Magnitudes of Odds Ratios in Epidemiological Studies

Chen, H., Cohen, P., & Chen, S. (2010) · Communications in Statistics - Simulation and Computation · doi:10.1080/03610911003650383 · Cited by 1,952

An Introduction to Logistic Regression Analysis and Reporting

Peng, C.-Y. J., Lee, K. L., & Ingersoll, G. M. (2002) · The Journal of Educational Research · doi:10.1080/00220670209598786 · Cited by 2,671

Multifactor-Dimensionality Reduction Reveals High-Order Interactions among Estrogen-Metabolism Genes in Sporadic Breast Cancer

Ritchie, M. D., Hahn, L. W., Roodi, N., Bailey, L., Dupont, W. D., Parl, F. F., & Moore, J. H. (2001) · The American Journal of Human Genetics · doi:10.1086/321276 · Cited by 1,899

Predicting chemotherapy toxicity in older adults with cancer: a prospective multicenter study

Hurria, A., Togawa, K., Mohile, S. G., Owusu, C., Klepin, H. D., Gross, C. P., Lichtman, S. M., Gajra, A., Bhatia, S., Katheria, V., et al. (2011) · Journal of Clinical Oncology · doi:10.1200/jco.2011.34.7625 · Cited by 1,841

Understanding the minimum clinically important difference: A review of concepts and methods

Copay, A. G., Subach, B. R., Glassman, S. D., Polly, D. W., & Schuler, T. C. (2007) · The Spine Journal · doi:10.1016/j.spinee.2007.01.008 · Cited by 1,662

A brief conceptual tutorial of multilevel analysis in social epidemiology: using measures of clustering in multilevel logistic regression to investigate contextual phenomena

Merlo, J., Chaix, B., Ohlsson, H., Beckman, A., Johnell, K., Hjerpe, P., Råstam, L., & Larsen, K. (2006) · Journal of Epidemiology & Community Health · doi:10.1136/jech.2004.029454 · Cited by 1,682

Machine learning for medical imaging

Erickson, B. J., Korfiatis, P., Akkus, Z., & Kline, T. L. (2017) · RadioGraphics · doi:10.1148/rg.2017160130 · Cited by 1,672

Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications

Lee, J., Wu, F., Zhao, W., Ghaffari, M., Liao, L., & Siegel, D. (2013) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2013.06.004 · Cited by 1,723

Corporate Governance and Accounting Scandals

Agrawal, A., & Chadha, S. (2005) · The Journal of Law and Economics · doi:10.1086/430808 · Cited by 1,528

Plasma MicroRNA Profiling Reveals Loss of Endothelial MiR-126 and Other MicroRNAs in Type 2 Diabetes

Zampetaki, A., Kiechl, S., Drozdov, I., Willeit, P., Mayr, U., Prokopi, M., Mayr, A., Weger, S., Oberhollenzer, F., Bonora, E., et al. (2010) · Circulation Research · doi:10.1161/circresaha.110.226357 · Cited by 1,283

A new approach to cross-modal multimedia retrieval

Rasiwasia, N., Pereira, J. C., Coviello, E., Doyle, G., Lanckriet, G. R. G., Lévy, R., & Vasconcelos, N. M. (2010) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/1873951.1873987 · Cited by 1,361

Logistic Regression: A Brief Primer

Stoltzfus, J. C. (2011) · Academic Emergency Medicine · doi:10.1111/j.1553-2712.2011.01185.x · Cited by 1,290

The Diagnosis of Bronchopulmonary Dysplasia in Very Preterm Infants. An Evidence-based Approach

Jensen, E. A., Dysart, K., Gantz, M. G., McDonald, S. A., Bamat, N. A., Keszler, M., Kirpalani, H. M., Laughon, M. M., Poindexter, B. B., Duncan, A. F., et al. (2019) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201812-2348oc · Cited by 1,274

Physical performance measures in the clinical setting

Studenski, S., Perera, S., Wallace, D., Chandler, J. M., Duncan, P. W., Rooney, E., Fox, M., & Guralnik, J. M. (2003) · Journal of the American Geriatrics Society · doi:10.1046/j.1532-5415.2003.51104.x · Cited by 1,218

Fully conditional specification in multivariate imputation

Van Buuren, S., Brand, J. P. L., Groothuis-Oudshoorn, C. G. M., & Rubin, D. B. (2006) · Journal of Statistical Computation and Simulation · doi:10.1080/10629360600810434 · Cited by 1,217

Tests of the three-path mediated effect

Taylor, A. B., MacKinnon, D. P., & Tein, J.-Y. (2008) · Organizational Research Methods · doi:10.1177/1094428107300344 · Cited by 1,209

Logistic Regression

LaValley, M. P. (2008) · Circulation · doi:10.1161/circulationaha.106.682658 · Cited by 1,163

Predicting the risk of chemotherapy toxicity in older patients: The Chemotherapy Risk Assessment Scale for High‐Age Patients (CRASH) score

Extermann, M., Boler, I., Reich, R. R., Lyman, G. H., Brown, R. H., DeFelice, J., Levine, R. M., Lubiner, E. T., Reyes, P., Schreiber Frederic, J., et al. (2011) · Cancer · doi:10.1002/cncr.26646 · Cited by 1,147

Continuous insulin infusion reduces mortality in patients with diabetes undergoing coronary artery bypass grafting

Furnary, A. P., Gao, G., Grunkemeier, G. L., Wu, Y., Zerr, K. J., Bookin, S. O., Floten, H. S., & Starr, A. (2003) · The Journal of Thoracic and Cardiovascular Surgery · doi:10.1067/mtc.2003.181 · Cited by 1,130

25-Hydroxyvitamin D and Risk of Myocardial Infarction in Men A Prospective Study

Giovannucci, E. L. (2008) · Archives of Internal Medicine · doi:10.1001/archinte.168.11.1174 · Cited by 1,145

Multifactor dimensionality reduction software for detecting gene–gene and gene–environment interactions

Hahn, L. W., Ritchie, M. D., & Moore, J. H. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btf869 · Cited by 1,134

Mucosal Healing in Inflammatory Bowel Disease: Results From a Norwegian Population-Based Cohort

Frøslie, K. F., Jahnsen, J., Moum, B. A., & Vatn, M. H. (2007) · Gastroenterology · doi:10.1053/j.gastro.2007.05.051 · Cited by 1,121

Predicting aberrant behaviors in opioid-treated patients: preliminary validation of the Opioid Risk Tool

Webster, L. R., & Webster, R. M. (2005) · Pain Medicine · doi:10.1111/j.1526-4637.2005.00072.x · Cited by 1,096

Categorical Data Analysis

Agresti, A., & Kateri, M. (2011) · International Encyclopedia of Statistical Science · doi:10.1007/978-3-642-04898-2_161 · Cited by 1,112

Collinearity diagnostics of binary logistic regression model

Midi, H., Sarkar, S. K., & Rana, S. (2010) · Journal of Interdisciplinary Mathematics · doi:10.1080/09720502.2010.10700699 · Cited by 1,107

Visualization of Regression Models Using visreg

Breheny, P. J., & Burchett, W. (2017) · The R Journal · doi:10.32614/rj-2017-046 · Cited by 1,102

A primary care back pain screening tool: identifying patient subgroups for initial treatment

Hill, J. C., Dunn, K. M., Lewis, M., Mullis, R., Main, C. J., Foster, N. E., & Hay, E. M. (2008) · Arthritis Care & Research · doi:10.1002/art.23563 · Cited by 1,052

Progesterone and the Risk of Preterm Birth among Women with a Short Cervix

da Fonseca, E. B., Çelik, E., Parra, M., Singh, M., & Nicolaides, K. H. (2007) · New England Journal of Medicine · doi:10.1056/nejmoa067815 · Cited by 1,090

PIM2: a revised version of the Paediatric Index of Mortality

for the PIM Study Group, Slater, A., Shann, F. A., & Pearson, G. A. (2003) · Intensive Care Medicine · doi:10.1007/s00134-002-1601-2 · Cited by 1,068

Pipeline persistence: Examining the association of educational experiences with earned degrees in STEM among U.S. students

Maltese, A., & Tai, R. H. (2011) · Science Education · doi:10.1002/sce.20441 · Cited by 1,101

Electronic business adoption by European firms: a cross-country assessment of the facilitators and inhibitors

Zhu, K., Kraemer, K., & Xu, S. (2003) · European Journal of Information Systems · doi:10.1057/palgrave.ejis.3000475 · Cited by 1,043

Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): Explanation and Elaboration

Altman, D. G., McShane, L. M., Sauerbrei, W., & Taube, S. E. (2012) · PLoS Medicine · doi:10.1371/journal.pmed.1001216 · Cited by 1,034

Data mining for credit card fraud: a comparative study

Bhattacharyya, S., Jha, S., Tharakunnel, K., & Westland, J. C. (2011) · Decision Support Systems · doi:10.1016/j.dss.2010.08.008 · Cited by 1,108

Quantitative Analyses of SMN1 and SMN2 Based on Real-Time LightCycler PCR: Fast and Highly Reliable Carrier Testing and Prediction of Severity of Spinal Muscular Atrophy

Feldkötter, M., Schwarzer, V., Wirth, R., Wienker, T. F., & Wirth, B. (2002) · The American Journal of Human Genetics · doi:10.1086/338627 · Cited by 1,005

Global Pyrogeography: the Current and Future Distribution of Wildfire

Krawchuk, M. A., Moritz, M. A., Parisien, M.-A., Van Dorn, J., & Hayhoe, K. (2009) · PLoS ONE · doi:10.1371/journal.pone.0005102 · Cited by 1,000

Prevalence and Axis I comorbidity of full and partial posttraumatic stress disorder in the United States: results from Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions

Pietrzak, R. H., Goldstein, R. B., Southwick, S. M., & Grant, B. F. (2011) · Journal of Anxiety Disorders · doi:10.1016/j.janxdis.2010.11.010 · Cited by 963

Environmental Conditions Influence eDNA Persistence in Aquatic Systems

Barnes, M. A., Turner, C. R., Jerde, C. L., Renshaw, M. A., Chadderton, W. L., & Lodge, D. M. (2014) · Environmental Science & Technology · doi:10.1021/es404734p · Cited by 1,017

A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility

Chen, W., Xie, X., Wang, J., Pradhan, B., Hong, H., Bui, D. T., Duan, Z., & Ma, J. (2016) · CATENA · doi:10.1016/j.catena.2016.11.032 · Cited by 971

THE EFFECTS OF JOB EMBEDDEDNESS ON ORGANIZATIONAL CITIZENSHIP, JOB PERFORMANCE, VOLITIONAL ABSENCES, AND VOLUNTARY TURNOVER.

Lee, T. W., Mitchell, T. R., Sablynski, C. J., Burton, J. P., & Holtom, B. C. (2004) · Academy of Management Journal · doi:10.2307/20159613 · Cited by 927

External validation of a Cox prognostic model: principles and methods

Royston, P. J., & Altman, D. G. (2013) · BMC Medical Research Methodology · doi:10.1186/1471-2288-13-33 · Cited by 911

Groundwater Arsenic Contamination Throughout China

Rodríguez‐Lado, L., Sun, G., Berg, M. D. V., Zhang, Q., Xue, H., Zheng, Q., & Johnson, C. A. (2013) · Science · doi:10.1126/science.1237484 · Cited by 911

Empirical validation of object-oriented metrics on open source software for fault prediction

Gyimóthy, T., Ferenć, R., & Siket, I. (2005) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2005.112 · Cited by 904

Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker

Moons, K. G. M., Kengne, A. P., Woodward, M., Royston, P., Vergouwe, Y., Altman, D. G., & Grobbee, D. E. (2012) · Heart · doi:10.1136/heartjnl-2011-301246 · Cited by 889

Associations of Hormones and Menopausal Status With Depressed Mood in Women With No History of Depression

Freeman, E. W., Sammel, M. D., Lin, H., & Nelson, D. B. (2006) · Archives of General Psychiatry · doi:10.1001/archpsyc.63.4.375 · Cited by 921

Classification and regression tree analysis in public health: Methodological review and comparison with logistic regression

Lemon, S. C., Roy, J., Clark, M. A., Friedmann, P. D., & Rakowski, W. (2003) · Annals of Behavioral Medicine · doi:10.1207/s15324796abm2603_02 · Cited by 898

Chief Executive Officer Equity Incentives and Accounting Irregularities

Armstrong, C., Jagolinzer, A. D., & Larcker, D. F. (2009) · Journal of Accounting Research · doi:10.1111/j.1475-679x.2009.00361.x · Cited by 882

Ad click prediction

McMahan, H. B., Holt, G., Sculley, D., Young, M., Ebner, D., Grady, J., Nie, L., Phillips, T., Davydov, E. V., Golovin, D., et al. (2013) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/2487575.2488200 · Cited by 870

Myocardial Iodine-123 Meta-Iodobenzylguanidine Imaging and Cardiac Events in Heart Failure

Jacobson, A. F., Senior, R., Cerqueira, M. D., Wong, N. D., Thomas, G. S., López, V. A., Agostini, D., Weiland, F., Chandna, H., & Narula, J. (2010) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2010.01.014 · Cited by 867

Identifying critically ill patients who benefit the most from nutrition therapy: the development and initial validation of a novel risk assessment tool

Heyland, D. K., Dhaliwal, R., Jiang, X., & Day, A. G. (2011) · Critical Care · doi:10.1186/cc10546 · Cited by 863

How to do Linguistics with R

Levshina, N. (2015) · John Benjamins Publishing Company eBooks · doi:10.1075/z.195 · Cited by 862

Measuring Securities Litigation Risk

Kim, I., & Skinner, D. J. (2011) · Journal of Accounting and Economics · doi:10.1016/j.jacceco.2011.09.005 · Cited by 848

Longitudinal and Panel Data

Frees, E. W. (2004) · Cambridge University Press eBooks · doi:10.1017/cbo9780511790928 · Cited by 872

Depression and anxiety among university students during the COVID-19 pandemic in Bangladesh: A web-based cross-sectional survey

Islam, M. A., Barna, S. D., Raihan, H., Khan, M. N. A., & Hossain, M. T. (2020) · PLOS ONE · doi:10.1371/journal.pone.0238162 · Cited by 834

Evaluating machine learning and statistical prediction techniques for landslide susceptibility modeling

Goetz, J. N., Brenning, A., Petschko, H., & Leopold, P. (2015) · Computers & Geosciences · doi:10.1016/j.cageo.2015.04.007 · Cited by 846

Application of random effects to the study of resource selection by animals

Gillies, C. S., Hebblewhite, M., Nielsen, S. E., Krawchuk, M. A., Aldridge, C. L., Frair, J. L., Saher, D. J., Stevens, C. E., & Jerde, C. L. (2006) · Journal of Animal Ecology · doi:10.1111/j.1365-2656.2006.01106.x · Cited by 811

Personality and Politics: Values, Traits, and Political Choice

Caprara, G. V., Schwartz, S. H., Capanna, C., Vecchione, M., & Barbaranelli, C. (2006) · Political Psychology · doi:10.1111/j.1467-9221.2006.00447.x · Cited by 812

The epidemiology of panic attacks, panic disorder, and agoraphobia in the National Comorbidity Survey Replication

Kessler, R. C., Chiu, W. T., Jin, R., Ruscio, A. M., Shear, K., & Walters, E. E. (2006) · Archives of General Psychiatry · doi:10.1001/archpsyc.63.4.415 · Cited by 795

Toward a global view of alcohol, tobacco, cannabis, and cocaine use: findings from the WHO world mental health surveys

Degenhardt, L., Chiu, W.-T., Sampson, N., Kessler, R. C., Anthony, J. C., Angermeyer, M., Bruffaerts, R., de Girolamo, G., Gureje, O., Huang, Y., et al. (2008) · PLoS Medicine · doi:10.1371/journal.pmed.0050141 · Cited by 796

Audit Committee Quality, Auditor Independence, and Internal Control Weaknesses

Zhang, Y., Zhou, J. T., & Zhou, N. (2006) · Journal of Accounting and Public Policy · doi:10.1016/j.jaccpubpol.2007.03.001 · Cited by 776

Automated reverse engineering of nonlinear dynamical systems

Bongard, J., & Lipson, H. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0609476104 · Cited by 792

American Academy of Clinical Neuropsychology Consensus Conference Statement on the Neuropsychological Assessment of Effort, Response Bias, and Malingering

Heilbronner, R. L., Sweet, J. J., Morgan, J. E., Larrabee, G. J., Millis, S. R., & Participants1, C. (2009) · The Clinical Neuropsychologist · doi:10.1080/13854040903155063 · Cited by 869

Passive Immunization during Pregnancy for Congenital Cytomegalovirus Infection

Nigro, G., Adler, S. P., Torre, R. L., & Best, A. M. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa043337 · Cited by 776

Distress about sex: a national survey of women in heterosexual relationships.

Bancroft, J., Loftus, J., & Long, J. S. (2003) · Archives of Sexual Behavior · doi:10.1023/a:1023420431760 · Cited by 774

Landslide susceptibility mapping using random forest, boosted regression tree, classification and regression tree, and general linear models and comparison of their performance at Wadi Tayyah Basin, Asir Region, Saudi Arabia

Youssef, A. M., Pourghasemi, H. R., Pourtaghi, Z. S., & Al-Katheri, M. M. (2015) · Landslides · doi:10.1007/s10346-015-0614-1 · Cited by 772

Antithrombotic Therapy in Atrial Fibrillation

Singer, D. E., Albers, G. W., Dalen, J. E., Fang, M. C., Go, A. S., Halperin, J. L., Lip, G. Y. H., & Manning, W. J. (2008) · CHEST Journal · doi:10.1378/chest.08-0678 · Cited by 758

Gait Speed as an Incremental Predictor of Mortality and Major Morbidity in Elderly Patients Undergoing Cardiac Surgery

Afilalo, J., Eisenberg, M. J., Morin, J.-F., Bergman, H., Monette, J., Noiseux, N., Perrault, L. P., Alexander, K. P., Langlois, Y., Dendukuri, N., et al. (2010) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2010.06.039 · Cited by 746

Association of Hemoglobin Levels With Clinical Outcomes in Acute Coronary Syndromes

Sabatine, M. S., Morrow, D. A., Giugliano, R. P., Burton, P. B. J., Murphy, S. A., McCabe, C. H., Gibson, C. M., & D, E. B. M. (2005) · Circulation · doi:10.1161/01.cir.0000162477.70955.5f · Cited by 736

Cytokine profiles as markers of disease severity in sepsis: a multiplex analysis

Bozza, F. A., Salluh, J. I., Japiassú, A. M., Soares, M., de Assis, E. F., Gomes, R. N., Bozza, M. T., Castro-Faria-Neto, H. C., & Bozza, P. T. (2007) · Critical Care · doi:10.1186/cc5783 · Cited by 740

An experimental comparison of classification algorithms for imbalanced credit scoring data sets

Brown, I., & Mues, C. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2011.09.033 · Cited by 813

Earnings Management: New Evidence Based on Deferred Tax Expense

Phillips, J. D., Pincus, M., & Rego, S. O. (2003) · The Accounting Review · doi:10.2308/accr.2003.78.2.491 · Cited by 726

Statistics review 14: Logistic regression.

Bewick, V., Cheek, L., & Ball, J. (2005) · Critical Care · doi:10.1186/cc3045 · Cited by 716

Rescuers at risk: a systematic review and meta-regression analysis of the worldwide current prevalence and correlates of PTSD in rescue workers

Berger, W., Coutinho, E. S. F., Figueira, I., Marques-Portella, C., Luz, M. P., Neylan, T. C., Marmar, C. R., & Mendlowicz, M. V. (2012) · Social Psychiatry and Psychiatric Epidemiology · doi:10.1007/s00127-011-0408-2 · Cited by 712

Performance of Comorbidity Scores to Control for Confounding in Epidemiologic Studies using Claims Data

Schneeweiß, S. (2001) · American Journal of Epidemiology · doi:10.1093/aje/154.9.854 · Cited by 712

Audit Firm Tenure and Fraudulent Financial Reporting

Carcello, J. V., & Nagy, A. L. (2004) · Auditing A Journal of Practice & Theory · doi:10.2308/aud.2004.23.2.55 · Cited by 706

Cardiovascular Risk Prediction: Basic Concepts, Current Status, and Future Directions

Lloyd-Jones, D. M. (2010) · Circulation · doi:10.1161/circulationaha.109.849166 · Cited by 705

Widespread deoxygenation of temperate lakes

Jane, S. F., Hansen, G. J. A., Kraemer, B. M., Leavitt, P. R., Mincer, J. L., North, R. L., Pilla, R. M., Stetler, J. T., Williamson, C. E., Woolway, R. I., et al. (2021) · Nature · doi:10.1038/s41586-021-03550-y · Cited by 716

Landslide susceptibility estimation by random forests technique: sensitivity and scaling issues

Catani, F., Lagomarsino, D., Segoni, S., & Tofani, V. (2013) · Natural hazards and earth system sciences · doi:10.5194/nhess-13-2815-2013 · Cited by 713

Association of Racial/Ethnic and Gender Concordance Between Patients and Physicians With Patient Experience Ratings

Takeshita, J., Wang, S., Loren, A. W., Mitra, N., Shults, J., Shin, D. B., & Sawinski, D. L. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.24583 · Cited by 697

Prevalence of Nontuberculous Mycobacterial Lung Disease in U.S. Medicare Beneficiaries

Adjemian, J., Olivier, K. N., Seitz, A. E., Holland, S. M., & Prevots, D. R. (2012) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201111-2016oc · Cited by 691

A meta-analytic review of obesity prevention programs for children and adolescents: The skinny on interventions that work.

Stice, E. M., Shaw, H. E., & Marti, C. N. (2006) · Psychological Bulletin · doi:10.1037/0033-2909.132.5.667 · Cited by 718

Learning analytics should not promote one size fits all: The effects of instructional conditions in predicting academic success

Gašević, D., Dawson, S., Rogers, T., & Gašević, D. (2015) · The Internet and Higher Education · doi:10.1016/j.iheduc.2015.10.002 · Cited by 767

The extent and nature of opportunity identification by experienced entrepreneurs

Ucbasaran, D., Westhead, P., & Wright, M. (2008) · Journal of Business Venturing · doi:10.1016/j.jbusvent.2008.01.008 · Cited by 718

Spatial prediction models for landslide hazards: review, comparison and evaluation

Brenning, A. (2005) · Natural hazards and earth system sciences · doi:10.5194/nhess-5-853-2005 · Cited by 698

Basic Personal Values, Core Political Values, and Voting: A Longitudinal Analysis

Schwartz, S. H., Caprara, G. V., & Vecchione, M. (2010) · Political Psychology · doi:10.1111/j.1467-9221.2010.00764.x · Cited by 673

A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods

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