Nonparametric bootstrapping for hierarchical data

An Introduction to the Bootstrap

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An Introduction to the Bootstrap

Efron, B., & Tibshirani, R. J. (1993) · doi:10.1007/978-1-4899-4541-9 · Cited by 21,230

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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Bootstrap Methods and their Application

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Bootstrap Methods and Their Application

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Multilevel Statistical Models

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Multilevel Statistical Models

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Fingerprint resampling: A generic method for efficient resampling

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Generating complex networks with time-to-control communities

Ramos, G., & Pequito, S. (2020) · PLoS ONE · doi:10.1371/journal.pone.0236753 · Cited by 4

Strategic Responses to Peer-Firm Financial Flexibility: Evidence from Indirect Treatment EffectsPreprint

Nordlund, J. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2866505 · Cited by 4

Higher general intelligence is associated with stable, efficient, and typical dynamic functional brain connectivity patterns

Ng, J., Yu, J., Feusner, J. D., & Hawco, C. S. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00234 · Cited by 3

Clinical Practice Guideline-Inconsistent Management of Fertility Preservation in Pediatric Cancer Patients in Community Settings: A Children’s Oncology Group Study

Grimes, A. C., Sugalski, A., Nuño, M. M., Ramakrishnan, S., Beauchemin, M., Robinson, P., Santesso, N., Walsh, A. M., Wrightson, A. R., Yu, L.-L. C., et al. (2024) · Journal of Adolescent and Young Adult Oncology · doi:10.1089/jayao.2024.0022 · Cited by 2

Western gray squirrel resource selection related to fire fuel management

Stuart, K. D., Haegen, W. M. V., Jenkins, K. J., Keren, I. N., & West, S. D. (2018) · Journal of Wildlife Management · doi:10.1002/jwmg.21499 · Cited by 3

Multilevel Modeling When the Effects of Lower-Level Variables Vary Across Clusters. A Monte-Carlo Comparison of Mixed-Effects Models, Cluster-Robust Pooled OLS and Two-Step EstimationPreprint

Heisig, J. P., Schaeffer, M., & Giesecke, J. A. (2015) · SSRN Electronic Journal · doi:10.2139/ssrn.2703431 · Cited by 3

Longitudinal regression of covariance matrix outcomes

Zhao, Y., Caffo, B. S., & Luo, X. (2022) · Biostatistics · doi:10.1093/biostatistics/kxac045 · Cited by 2

Cost-effectiveness of monthly follow-up for the treatment of uncomplicated severe acute malnutrition: An economic evaluation of a randomized controlled trial

Menzies, N. A., Berthé, F., Hitchings, M. D. T., Aruna, P., Hamza, M. A., Nanama, S., Steve-Edemba, C., Shehu, I., Grais, R. F., & Isanaka, S. (2022) · PLOS Global Public Health · doi:10.1371/journal.pgph.0001189 · Cited by 2

Semiparametric estimation for nonparametric frailty models using nonparametric maximum likelihood approach

Chee, C.-S., Ha, I. D., Seo, B., & Lee, Y. (2021) · Statistical Methods in Medical Research · doi:10.1177/09622802211037072 · Cited by 2

Statistical Analysis Plan for the manuscript reporting the primary outcome of the MSU-TELEMED studyPreprint

Churilov, L. P., Johns, H. T., Yogendrakumar, V., Balabanski, A. H., & MSU-TELEMED Trial Investigators (2025) · medRxiv · doi:10.1101/2025.02.11.25322103 · Cited by 2

Horizontal Transport of Picture Gorge Basalt Magma Through the Monument Dike Swarm Determined by Magnetic Fabric

Avery, M. S., & Pivarunas, A. F. (2025) · Geochemistry Geophysics Geosystems · doi:10.1029/2024gc012078 · Cited by 1

Covariance-on-covariance regression

Zhao, Y., & Zhao, Y. (2025) · Biometrics · doi:10.1093/biomtc/ujaf097 · Cited by 1

Assessing Stability in NonLinear PCA with Hierarchical Data

Manisera, M. (2013) · Studies in classification, data analysis, and knowledge organization · doi:10.1007/978-3-319-00032-9_25 · Cited by 1

Within-Hospital Variation in 30-Day Adverse Events: Implications for Measuring Quality

Burke, R. E., Glorioso, T. J., Barón, A. K., Kaboli, P. J., & Ho, P. M. (2017) · Journal for Healthcare Quality · doi:10.1097/jhq.0000000000000086 · Cited by 1

Hierarchical time-varying mixed-effects models in high-dimensional time series and longitudinal data studies

Jinglan, L., & Zhang, Z. (2019) · Journal of nonparametric statistics · doi:10.1080/10485252.2019.1629436 · Cited by 1

Examining the Relationship Between Multilevel Resilience Resources and Cardiovascular Disease Incidence, Overall and by Psychosocial Risks, Among Participants in the Jackson Heart Study, the Multi-Ethnic Study of Atherosclerosis, and the Mediators of Atherosclerosis in South Asians Living in America (MASALA) Study

Park, J. W., Dulin, A., Scarpaci, M. M., Dionne, L. A., Needham, B. L., Sims, M., Kanaya, A. M., Kandula, N. R., Loucks, E. B., Fava, J. L., et al. (2023) · American Journal of Epidemiology · doi:10.1093/aje/kwad159 · Cited by 1

Estimating flood recurrence uncertainty for non-stationary regimes

Gomes, Y. R. M., Marques, L. D. A., & Souza, C. F. (2023) · Revista Brasileira de Recursos Hídricos · doi:10.1590/2318-0331.282320230031 · Cited by 1

Developing methods for causal mediation analysis of parenting interventions to improve child antisocial behaviour

Zhang, C. (2015) · Cited by 1

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

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. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.02.06.479292 · Cited by 1

Single-cell differential expression analysis between conditions within nested settingsPreprint

Hafner, L., Sturm, G., & List, M. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.08.01.606200 · Cited by 1

Efficient strategies for collecting posture data using observation and direct measurement

Liv, P. (2012) · DiVA at Umeå University (Umeå University)

Original Article Standardizing compositional data for stock assessment

Thorson, J. T. (2014)

How do Consumers Form Online Search Queries? The Importance of Activation Probabilities between Queries and ResultsPreprint

Liu, J., & Toubia, O. (2015) · SSRN Electronic Journal · doi:10.2139/ssrn.2675331

Evaluation of a length-based method to estimate discard rate and the effect of sampling sizePreprint

Sturludóttir, E., Sigurðsson, G. M., & Stefánsson, G. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1902.10579

Admissible dissimilarity value (ADV) as a measure of subsampling reliability: case study North Sea cod (Gadus morhua)

Wischnewski, J., Bernreuther, M., & Kempf, A. (2020) · Environmental Monitoring and Assessment · doi:10.1007/s10661-020-08668-6

Semiparametric inference for proportional mean residual life models with clustered survival data

Huang, R. (2020) · doi:10.32657/10356/143100

Upstrap for Estimating Power and Sample Size in Complex ModelsPreprint

Karas, M., & Crainiceanu, C. M. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.08.21.457220

Estimating reference intervals from an IPD meta-analysis using quantile regression

Jiang, Z., Chu, H., Wang, Z., Murad, M. H., & Siegel, L. K. (2024) · BMC Medical Research Methodology · doi:10.1186/s12874-024-02378-0

Representative sampling by fishers in a reference fleet programme

Clegg, T. L. (2025) · Fisheries Research · doi:10.1016/j.fishres.2025.107342

Supplementary material to "Global observations of land-atmosphere interactions during flash drought"

Harris, B. L., Taylor, C. M., Dorigo, W. A., Zotta, R.-M., Ghent, D. J., & Noguera, I. (2025) · doi:10.5194/egusphere-2025-1489-supplement

Predicting Hospital Admissions Using Pretrained EHR Embeddings: External Evaluation and Insights on Local Vocabulary AdaptationPreprint

Neves, B. D., Cerejo, J., Gonçalves, S., Mota, I., Moreira, J. M., Silva, N. A., Leite, F., Wornow, M., & Silva, M. J. (2025) · medRxiv · doi:10.1101/2025.09.08.25335368

Practical inference for a complier average causal effect in cluster randomised trials with a binary outcome

Edwards, T., Thompson, J. A., Opondo, C., & Allen, E. (2025) · Clinical Trials · doi:10.1177/17407745251378407

Additional file 1 of Evaluating a multimodal, clinical and work-directed intervention (RTW-PIA) to support sustainable return to work among employees with mental disorders: study protocol of a multicentre, randomised controlled trial

Starke, F., Sikora, A., Stegmann, R., Knebel, L., Buntrock, C., de Rijk, A. E., Houkes, I., Szycik, G. R., Unger, H.-P., Schumacher, J. O., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26592956

Additional file 2 of Evaluating a multimodal, clinical and work-directed intervention (RTW-PIA) to support sustainable return to work among employees with mental disorders: study protocol of a multicentre, randomised controlled trial

Starke, F., Sikora, A., Stegmann, R., Knebel, L., Buntrock, C., de Rijk, A. E., Houkes, I., Szycik, G. R., Unger, H.-P., Schumacher, J. O., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26592959

Additional file 2 of 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

Schaub, T., Millon, A., Zutter, C. D., Buij, R., Chadœuf, J., Lee, S., Mionnet, A., & Klaassen, R. H. G. (2023) · Figshare · doi:10.6084/m9.figshare.23884409

Additional file 4 of 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

Schaub, T., Millon, A., Zutter, C. D., Buij, R., Chadœuf, J., Lee, S., Mionnet, A., & Klaassen, R. H. G. (2023) · Figshare · doi:10.6084/m9.figshare.23884415

Additional file 3 of 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

Schaub, T., Millon, A., Zutter, C. D., Buij, R., Chadœuf, J., Lee, S., Mionnet, A., & Klaassen, R. H. G. (2023) · Figshare · doi:10.6084/m9.figshare.23884412

Additional file 1 of 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) · Figshare · doi:10.6084/m9.figshare.18517561

Additional file 1 of 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., Domschke, K., Ebert, D. D., Ell, J., Janneck, M., Jenkner, C., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26731849

Additional file 1 of 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

Schaub, T., Millon, A., Zutter, C. D., Buij, R., Chadœuf, J., Lee, S., Mionnet, A., & Klaassen, R. H. G. (2023) · Figshare · doi:10.6084/m9.figshare.23884406

Applying the Target Study Conceptual Model to Measure Racial and Ethnic Disparities in Hypertension Treatment Intensification

Meche, A., Boonyasai, R. T., Hsu, Y., Greer, R. C., Mehta, H., Alexander, G. C., Segal, J. B., Cooper, L. A., & Jackson, J. W. (2026) · Epidemiology · doi:10.1097/ede.0000000000001964

Mécanismes cognitifs et psycho-sociaux impliqués dans l'apprentissage coopératif Jigsaw : études expérimentales en milieu scolaire

Vives, E. (2021) · theses.fr (ABES) · doi:10.70675/2fb05ffaz7d91z48e9zb682z275c895f4859

Comparing modeling approaches and sample sizes for bark thickness and volume among species and stand origin in Türkiye

Yang, S.-I., Özçelík, R., & Yavuz, H. (2026) · Forest Ecosystems · doi:10.1016/j.fecs.2026.100500

Medical data analysis support

Malinowski, K. P., & Szafarczyk, M. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-44570-5.00008-2

Occupational sex segregation is strongly predicted by psychological sex differences

Frostegård, J. K. E., Persson, B. N., Sorjonen, K., Hedebrant, K., Lundqvist, M., & Herlitz, A. (2026) · Scientific Reports · doi:10.1038/s41598-026-75691-x

A statistical model of in-situ vibration sensor detection performance in water distribution pipe networks

Mendis, R., Bergmann, D., Boley, M., Crook, J., & Tack, G. (2026) · Journal of Hydroinformatics · doi:10.2166/hydro.2026.177

Zrównanie ekwicentylowe na tle innych metod zrównywania na przykładzie sprawdzianu i egzaminu gimnazjalnego

Wołodźko, T., Kondratek, B., & Szaleniec, H. (2014) · Jagiellonian Digital Library (Jagiellonian University)

Bootstrap confidence intervals for generalized linear mixed models in dose-response analysis

Fatoretto, M. B., Demétrio, C., Brophy, C., & Moral, R. D. A. (2026) · Journal of Statistical Computation and Simulation · doi:10.1080/00949655.2026.2677023

Bootstrapping within the Multilevel/Hierarchical Linear Modeling Framework: A Primer for Use with SAS and SPLUS

Kyle, J., & Fan, R. X. (2015)

Nonparametric bootstrap methods for finite populations

Manzi, G. (2007)

The jackknife, thebootstrap and othernonparametric methods

Φράγκος, Χ. Κ. (2015)

The “New” Statistics: Resampling and Bootstrapping

Pace, L. A. (2012) · Apress eBooks · doi:10.1007/978-1-4302-4555-1_18 · Cited by 2