Nonparametric bootstrapping for hierarchical data

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An Introduction to the Bootstrap

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Bootstrap methods: another look at the jackknife

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Mixed-Effects Models in Sand S-PLUS

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Mixed-Effects Models in S and S-PLUS

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Recommendations for Quantitation of the Left Ventricle by Two-Dimensional Echocardiography

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Multilevel Statistical Models

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Multilevel Statistical Models

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Development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal images from multiethnic populations with diabetes

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The correlations and sequence of plant stomatal, hydraulic, and wilting responses to drought

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Global analysis of plasticity in turgor loss point, a key drought tolerance trait

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Large-scale analysis of counseling conversations: an application of natural language processing to mental health

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Extending research on Emotion Regulation Individual Therapy for Adolescents (ERITA) with nonsuicidal self-injury disorder: open pilot trial and mediation analysis of a novel online version

Bjureberg, J., Sahlin, H., Hedman-Lagerlöf, E., Gratz, K. L., Tull, M. T., Jokinen, J., Hellner, C., & Ljótsson, B. (2018) · BMC Psychiatry · doi:10.1186/s12888-018-1885-6 · Cited by 96

Length and redundancy of outpatient progress notes across a decade at an academic medical center

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Measuring Hospital-Acquired Complications Associated With Low-Value Care

Badgery‐Parker, T., Pearson, S., Dunn, S., & Elshaug, A. G. (2019) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2018.7464 · Cited by 94

Cardiovascular brain impulses in Alzheimer’s disease

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Emotion regulation individual therapy for adolescents with nonsuicidal self-injury disorder: a feasibility study

Bjureberg, J., Sahlin, H., Hellner, C., Hedman-Lagerlöf, E., Gratz, K. L., Bjärehed, J., Jokinen, J., Tull, M. T., & Ljótsson, B. (2017) · BMC Psychiatry · doi:10.1186/s12888-017-1527-4 · Cited by 84

Prospective Study of a Multimodal Convulsive Seizure Detection Wearable System on Pediatric and Adult Patients in the Epilepsy Monitoring Unit

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Consistent stoichiometric long-term relationships between nutrients and chlorophyll-a across shallow lakes

Graeber, D., McCarthy, M. J., Shatwell, T., Borchardt, D., Jeppesen, E., Søndergaard, M., Lauridsen, T. L., & Davidson, T. A. (2024) · Nature Communications · doi:10.1038/s41467-024-45115-3 · Cited by 81

Testing the bargaining vs. inclusive fitness models of suicidal behavior against the ethnographic record

Syme, K., Garfield, Z. H., & Hagen, E. H. (2015) · Evolution and Human Behavior · doi:10.1016/j.evolhumbehav.2015.10.005 · Cited by 79

Propofol disrupts alpha dynamics in functionally distinct thalamocortical networks during loss of consciousness

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What to do when stopping over: behavioral decisions of a migrating songbird during stopover are dictated by initial change in their body condition and mediated by key environmental conditions

Smith, A. D., & McWilliams, S. (2014) · Behavioral Ecology · doi:10.1093/beheco/aru148 · Cited by 66

Effects of Study Population, Labeling and Training on Glaucoma Detection Using Deep Learning Algorithms

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Understanding Client Support Strategies to Improve Clinical Outcomes in an Online Mental Health Intervention

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Statistical power and validity of Ebola vaccine trials in Sierra Leone: a simulation study of trial design and analysis

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Software microbenchmarking in the cloud. How bad is it really?

Laaber, C., Scheuner, J., & Leitner, P. (2019) · Empirical Software Engineering · doi:10.1007/s10664-019-09681-1 · Cited by 64

Estimating uncertainty in respondent-driven sampling using a tree bootstrap method

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Bimodality and alternative equilibria do not help explain long-term patterns in shallow lake chlorophyll-a

Davidson, T. A., Sayer, C. D., Jeppesen, E., Søndergaard, M., Lauridsen, T. L., Johansson, L. S., Baker, A. G., & Graeber, D. (2023) · Nature Communications · doi:10.1038/s41467-023-36043-9 · Cited by 62

Alignment of galaxies relative to their local environment in SDSS-DR8

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Emotion regulation group therapy for deliberate self-harm: A multi-site evaluation in routine care using an uncontrolled open trial design

Sahlin, H., Bjureberg, J., Gratz, K. L., Tull, M. T., Hedman, E., Bjärehed, J., Jokinen, J., Lundh, L.-G., Ljótsson, B., & Hellner, C. (2017) · BMJ Open · doi:10.1136/bmjopen-2017-016220 · Cited by 50

Validating surgical procedure codes for inflammatory bowel disease in the Swedish National Patient Register

Forss, A., Myrelid, P., Olén, O., Everhov, A. H., Nordenvall, C. A. M., Halfvarson, J., & Ludvigsson, J. F. (2019) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-019-0948-z · Cited by 50

How Software Refactoring Impacts Execution Time

Traini, L., Pompeo, D. D., Tucci, M., Lin, B., Scalabrino, S., Bavota, G., Lanza, M., Oliveto, R., & Cortellessa, V. (2021) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3485136 · Cited by 47

Challenging Conventional Wisdom for Multivariate Statistical Models With Small Samples

McNeish, D. (2017) · Review of Educational Research · doi:10.3102/0034654317727727 · Cited by 54

A scoping review of statistical methods for trial‐based economic evaluations: The current state of play

Alili, M. E., van Dongen, J. M., Eßer, J., Heymans, M. W., van Tulder, M. W., & Bosmans, J. E. (2022) · Health Economics · doi:10.1002/hec.4603 · Cited by 41

Suitability of five cross validation methods for performance evaluation of nonlinear mixed-effects forest models - a case study

Yang, Y., & Huang, S. (2014) · Forestry An International Journal of Forest Research · doi:10.1093/forestry/cpu025 · Cited by 43

Dynamically reconfiguring software microbenchmarks: reducing execution time without sacrificing result quality

Laaber, C., Würsten, S., Gall, H. C., & Leitner, P. (2020) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3368089.3409683 · Cited by 39

Taking the Analysis of Trial-Based Economic Evaluations to the Next Level: The Importance of Accounting for Clustering

Alili, M. E., van Dongen, J. V., Goldfeld, K. S., Heymans, M., van Tulder, M. V., & Bosmans, J. (2020) · PharmacoEconomics (Auckland) · doi:10.1007/s40273-020-00946-y · Cited by 24

An Efficient Morris Method-Based Framework for Simulation Factor Screening

Shi, W., Chen, X., & Shang, J. S. (2019) · INFORMS journal on computing · doi:10.1287/ijoc.2018.0836 · Cited by 33

Nudging customers towards healthier food and beverage purchases in a real-life online supermarket: a multi-arm randomized controlled trial

Stuber, J. M., Lakerveld, J., Kievitsbosch, L. W., Mackenbach, J. D., & Beulens, J. W. J. (2022) · BMC Medicine · doi:10.1186/s12916-021-02205-z · Cited by 40

Clinical and Cost-Effectiveness of PSYCHOnlineTHERAPY: Study Protocol of a Multicenter Blended Outpatient Psychotherapy Cluster Randomized Controlled Trial for Patients With Depressive and Anxiety Disorders

Baumeister, H., Bauereiss, N., Zarski, A.-C., Braun, L., Buntrock, C., Hoherz, C., Idrees, A. R., Kraft, R., Meyer, P., Nguyen, T. B. D., et al. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.660534 · Cited by 30

Using structural restrictions to achieve theoretical consistency in benefit transfers

Newbold, S. C., Walsh, P. J., Massey, D. M., & Hewitt, J. (2018) · Environmental and Resource Economics · doi:10.1007/s10640-017-0209-5 · Cited by 32

Standardizing compositional data for stock assessment

Thorson, J. T. (2014) · ICES Journal of Marine Science · doi:10.1093/icesjms/fst224 · Cited by 31

Not just about the trees: Key role of mosaic-meadows in restoration of ponderosa pine ecosystems

Matonis, M., & Binkley, D. (2018) · Forest Ecology and Management · doi:10.1016/j.foreco.2018.01.019 · Cited by 30

Repeatability of Cone Spacing Measures in Eyes With Inherited Retinal Degenerations

Zayit‐Soudry, S., Sippl-Swezey, N., Porco, T. C., Lynch, S. K., Syed, R., Ratnam, K., Menghini, M., Roorda, A., & Duncan, J. L. (2015) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.15-17010 · Cited by 30

Reference effect measures for quantifying, comparing and visualizing variation from random and fixed effects in non-normal multilevel models, with applications to site variation in medical procedure use and outcomes

Glorioso, T. J., Grunwald, G. K., Ho, P. M., & Maddox, T. M. (2018) · BMC Medical Research Methodology · doi:10.1186/s12874-018-0517-7 · Cited by 27

Making social services work better for the poor: Evidence from a natural experiment with health sector decentralization in Honduras

Zarychta, A. (2020) · World Development · doi:10.1016/j.worlddev.2020.104996 · Cited by 30

Quantifying Performance Changes with Effect Size Confidence IntervalsPreprint

Kalibera, T., & Jones, R. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.10899 · Cited by 26

Importation, Antibiotics, and Clostridium difficile Infection in Veteran Long-Term Care

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Bayesian analysis of longitudinal and multidimensional functional data

Shamshoian, J., Şentürk, D., Jeste, S., & Telesca, D. (2020) · Biostatistics · doi:10.1093/biostatistics/kxaa041 · Cited by 21

Automated Generation and Evaluation of JMH Microbenchmark Suites From Unit Tests

Jangali, M., Tang, Y., Alexandersson, N., Leitner, P., Yang, J., & Shang, W. (2022) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2022.3188005 · Cited by 21

A Procedure and Guidelines for Analyzing Groups of Software Engineering Replications

Santos, A., Vegas, S., Oivo, M., & Juristo, N. (2019) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2019.2935720 · Cited by 23

Applying test case prioritization to software microbenchmarks

Laaber, C., Gall, H. C., & Leitner, P. (2021) · Empirical Software Engineering · doi:10.1007/s10664-021-10037-x · Cited by 20

How to improve the accuracy of height data from bird tracking devices? An assessment of high-frequency GPS tracking and barometric altimetry in field conditions

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Estimating maximum stand density for mixed-hardwood forests among various physiographic zones in the eastern US

Yang, S.-I., & Brandeis, T. J. (2022) · Forest Ecology and Management · doi:10.1016/j.foreco.2022.120420 · Cited by 18

Functional geometry of auditory cortical resting state networks derived from intracranial electrophysiology

Banks, M. I., Krause, B. M., Berger, D. G., Campbell, D. I., Boes, A. D., Bruss, J., Kovach, C. K., Kawasaki, H., Steinschneider, M., & Nourski, K. V. (2023) · PLoS Biology · doi:10.1371/journal.pbio.3002239 · Cited by 17

Comparative effectiveness of three versions of a stepped care model for insomnia differing in the amount of therapist support in internet-delivered treatment: study protocol for a pragmatic cluster randomised controlled trial (GET Sleep)

Spiegelhalder, K., Baumeister, H., Al-Kamaly, A., Bader, M., Bauereiß, N., Benz, F., Braun, L., Buntrock, C., Burkhardt, M., Cuijpers, P. J., et al. (2022) · BMJ Open · doi:10.1136/bmjopen-2021-058212 · Cited by 16

Faster or Slower? Performance Mystery of Python Idioms Unveiled with Empirical Evidence

Zhang, Z., Xing, Z., Xia, X., Xu, X., Zhu, L., & Lu, Q. (2023) · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) · doi:10.1109/icse48619.2023.00130 · Cited by 16

Evaluating Search-Based Software Microbenchmark Prioritization

Laaber, C., Yue, T., & Ali, S. (2024) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2024.3380836 · Cited by 16

Will Transformers change gastrointestinal endoscopic image analysis? A comparative analysis between CNNs and Transformers, in terms of performance, robustness and generalization

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Accuracy and precision of variance components in occupational posture recordings: a simulation study of different data collection strategies

Liv, P., Mathiassen, S. E., & Svendsen, S. W. (2012) · BMC Medical Research Methodology · doi:10.1186/1471-2288-12-58 · Cited by 16

How many crashes does cellphone use contribute to? Population attributable risk of cellphone use while driving

Guo, F., & Lu, D. (2022) · Journal of Safety Research · doi:10.1016/j.jsr.2022.07.005 · Cited by 16

Double Robust Estimation for Multiple Unordered Treatments and Clustered Observations: Evaluating Drug-Eluting Coronary Artery Stents

Rose, S., & Normand, S. T. (2018) · Biometrics · doi:10.1111/biom.12927 · Cited by 15

Predicting bark thickness with one- and two-stage regression models for three hardwood species in the southeastern US

Yang, S.-I., & Radtke, P. J. (2021) · Forest Ecology and Management · doi:10.1016/j.foreco.2021.119778 · Cited by 14

What do Danish children eat, and does the diet meet the recommendations? Baseline data from the OPUS School Meal Study

Andersen, R., Biltoft-Jensen, A. P., Christensen, T., Andersen, E. W., Ege, M., Thorsen, A. V., Knudsen, V. K., Damsgaard, C. T., Sørensen, L. B., Petersen, R. A., et al. (2015) · Journal of Nutritional Science · doi:10.1017/jns.2015.17 · Cited by 13

Evaluating semi- and nonparametric regression algorithms in quantifying stem taper and volume with alternative test data selection strategies

Yang, S.-I., Burkhart, H. E., & Seki, M. (2023) · Forestry An International Journal of Forest Research · doi:10.1093/forestry/cpad019 · Cited by 13

Biological variation: Evaluation of methods for constructing confidence intervals for estimates of within-person biological variation for different distributions of the within-person effect

Røraas, T., Støve, B., Petersen, P. H., & Sandberg, S. (2017) · Clinica Chimica Acta · doi:10.1016/j.cca.2017.02.021 · Cited by 13

Central tendency and matched difference approaches for assessing interrater agreement.

Burke, M. J., Cohen, A., Doveh, E., & Smith‐Crowe, K. (2018) · Journal of Applied Psychology · doi:10.1037/apl0000325 · Cited by 13

The Target Study: A Conceptual Model and Framework for Measuring Disparity

Jackson, J. W., Hsu, Y., Greer, R. C., Boonyasai, R. T., & Howe, C. J. (2025) · Sociological Methods & Research · doi:10.1177/00491241251314037 · Cited by 16

CAN QUASI‐EXPERIMENTAL EVALUATIONS THAT RELY ON STATE LONGITUDINAL DATA SYSTEMS REPLICATE EXPERIMENTAL RESULTS?

Unlu, F., Lauen, D. L., Fuller, S. C., Berglund, T., & Estrera, E. (2021) · Journal of Policy Analysis and Management · doi:10.1002/pam.22295 · Cited by 13

Quantification of Difference in Nonselectivity Between In Vitro Diagnostic Medical Devices

Fauskanger, P. K., Sandberg, S., Johansen, J. V., Keller, T., Budd, J. R., Miller, W. G., Stavelin, A. V., Delatour, V., Panteghini, M., & Støve, B. (2025) · Biometrical Journal · doi:10.1002/bimj.70032 · Cited by 10

Nonparametric Bootstrap Confidence Intervals for Variance Components Applied to Interlaboratory Comparisons

Burch, B. D. (2012) · Journal of Agricultural Biological and Environmental Statistics · doi:10.1007/s13253-012-0087-9 · Cited by 10

Single-cell differential expression analysis between conditions within nested settings

Hafner, L., Sturm, G., Lumpp, S., Drton, M., & List, M. (2025) · Briefings in Bioinformatics · doi:10.1093/bib/bbaf397 · Cited by 10

Frailty proportional mean residual life regression for clustered survival data: A hierarchical quasi‐likelihood method

Huang, R., Xiang, L., & Ha, I. D. (2019) · Statistics in Medicine · doi:10.1002/sim.8338 · Cited by 9

Growth dynamics and heritability for plant high‐throughput phenotyping studies using hierarchical functional data analysis

Xu, Y., Li, Y., & Qiu, Y. (2021) · Biometrical Journal · doi:10.1002/bimj.202000315 · Cited by 9

Analyzing Families of Experiments in SE: A Systematic Mapping Study

Santos, A., Gómez, O. S., & Juristo, N. (2018) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2018.2864633 · Cited by 10

Evaluating subscore uses across multiple levels: A case of reading and listening subscores for young EFL learners

Choi, I., & Papageorgiou, S. (2019) · Language Testing · doi:10.1177/0265532219879654 · Cited by 9

Adverse Events and Hospital-Acquired Conditions Associated With Potential Low-Value Care in Medicare Beneficiaries

Chalmers, K., Gopinath, V., Brownlee, S., Saini, V., & Elshaug, A. G. (2021) · JAMA Health Forum · doi:10.1001/jamahealthforum.2021.1719 · Cited by 9

A Cost–Consequence Analysis of Preemptive SLCO1B1 Testing for Statin Myopathy Risk Compared to Usual Care

Brunette, C. A., Dong, O. M., Vassy, J. L., Danowski, M. E., Alexander, N. V. J., Antwi, A. A., & Christensen, K. D. (2021) · Journal of Personalized Medicine · doi:10.3390/jpm11111123 · Cited by 9

Investigating non-inferiority of internet-delivered versus face-to-face cognitive behavioural therapy for insomnia (CBT-I): a randomised controlled trial (iSleep well)

Benz, F., Grolig, L., Hannibal, S., Buntrock, C., Cuijpers, P. J., Domschke, K., Ebert, D. D., Ell, J., Janneck, M., Jenkner, C., et al. (2024) · Trials · doi:10.1186/s13063-024-08214-6 · Cited by 10

Human-Guided Modality Informativeness for Affective States

Wörtwein, T., Sheeber, L., Allen, N. B., Cohn, J. F., & Morency, L. (2021) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/3462244.3481004 · Cited by 8

Split bootstrap hierarchical modeling of antibiotics abuse in China

Wang, B., Zheng, Y., Fang, D., Kamarianakis, Y., & Wilson, J. R. (2019) · Statistics in Medicine · doi:10.1002/sim.8118 · Cited by 8

Clinical practice guideline‐inconsistent chemotherapy‐induced vomiting prophylaxis in pediatric cancer patients in community settings: A Children's Oncology Group study

Sugalski, A., Grimes, A., Nuño, M. M., Ramakrishnan, S., Beauchemin, M., Robinson, P. D., Santesso, N. A., Walsh, A. M., Wrightson, A. R., Yu, L. C., et al. (2024) · Pediatric Blood & Cancer · doi:10.1002/pbc.31295 · Cited by 7

Response shift results of quantitative research using patient-reported outcome measures: a meta-regression analysis

Sawatzky, R. G., Verdam, M. G. E., Dubuy, Y., Sajobi, T. T., Russell, L. B., Awosoga, O., Ademola, A., Boehnke, J. R., Lawal, O. A., Brobbey, A., et al. (2024) · Quality of Life Research · doi:10.1007/s11136-024-03867-x · Cited by 7

Alternative fixed-effects panel model using weighted asymmetric least squares regression

Barry, A., Oualkacha, K., & Arthur Charpentier, A. (2023) · Statistical Methods & Applications · doi:10.1007/s10260-023-00692-3 · Cited by 7

Quantifying bark thickness and bark volume with alternative modeling procedures for eight species in the southeastern US

Yang, S.-I., & Qiao, Y. (2023) · Forest Ecology and Management · doi:10.1016/j.foreco.2023.121631 · Cited by 7

Behavioral Analysis of Vision-and-Language Navigation Agents

Yang, Z., Majumdar, A., & Lee, S. (2023) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52729.2023.00253 · Cited by 8

Explaining Within- vs Between-Population Variation in Child Anthropometry and Hemoglobin Measures in India: A Multilevel Analysis of the National Family Health Survey 2015–2016

Rodgers, J., Kim, R., & Subramanian, S. V. (2019) · Journal of Epidemiology · doi:10.2188/jea.je20190064 · Cited by 7

Using Variance to Explore the Diagnostic Utility of Baseline Concussion Testing

Rebchuk, A. D., Brown, H. J., Koehle, M. S., Blouin, J., & Siegmund, G. P. (2020) · Journal of Neurotrauma · doi:10.1089/neu.2019.6829 · Cited by 7

Monitoring tree occupancy and height in the Norwegian alpine treeline using a time series of airborne laser scanner data

Noordermeer, L., Bielza, J. C., Saarela, S., Gobakken, T., Bollandsås, O. M., & Næsset, E. (2023) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2023.103201 · Cited by 6

Clinical practice guideline‐inconsistent management of fever and neutropenia in pediatric oncology: A Children's Oncology Group study

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