On the Adaptive Control of the False Discovery Rate in Multiple Testing With Independent Statistics

Benjamini, Yoav; Hochberg, Yosef

doi:10.3102/10769986025001060

Cited by 2,015Statistical Methods in Clinical TrialsStatistical Methods and InferenceStatistical Methods and Bayesian Inference

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

On the Adaptive Control of the False Discovery Rate in Multiple Testing With Independent Statistics

Benjamini, Yoav, Hochberg, Yosef·2000·Journal of Educational and Behavioral Statistics

DOI 10.3102/10769986025001060

Open this paper in CoChat — free account

Abstract

A new approach to problems of multiple significance testing was presented in Benjamini and Hochberg (1995), which calls for controlling the expected ratio of the number of erroneous rejections to the number of rejections–the False Discovery Rate (FDR). The procedure given there was shown to control the FDR for independent test statistics. When some of the hypotheses are in fact false, that procedure is too conservative. We present here an adaptive procedure, where the number of true null hypotheses is estimated first as in Hochberg and Benjamini (1990), and this estimate is used in the procedure of Benjamini and Hochberg (1995). The result is still a simple stepwise procedure, to which we also give a graphical companion. The new procedure is used in several examples drawn from educational and behavioral studies, addressing problems in multi-center studies, subset analysis and meta-analysis. The examples vary in the number of hypotheses tested, and the implication of the new procedure on the conclusions. In a large simulation study of independent test statistics the adaptive procedure is shown to control the FDR and have substantially better power than the previously suggested FDR controlling method, which by itself is more powerful than the traditional family wise error-rate controlling methods. In cases where most of the tested hypotheses are far from being true there is hardly any penalty due to the simultaneous testing of many hypotheses.

Integrity signals

Registry

Crossref · 10.3102/10769986025001060

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

p-values were adjusted for multiple testing by controlling the false discovery rate according to the method of Benjamini and Hochberg.
“p-values were adjusted for multiple testing by controlling the false discovery rate (FDR) according to the method of Benjamini and Hochberg [44].”
From Shared and distinct microRNA profiles between HT22, N2A and SH-SY5Y cell lines and primary mouse hippocampal neurons (2025) · cites this paper as [44]
In mouse and rat hippocampal neurons, miR-103, miR-130a, miR-130b, miR-134, miR-376 and miR-449 are in the group with intermediate expression.
“and miR-103, miR-130a, miR-130b, miR-134, miR-376 and miR-449 are in the group with intermediate expression [44].”
From Shared and distinct microRNA profiles between HT22, N2A and SH-SY5Y cell lines and primary mouse hippocampal neurons (2025) · cites this paper as [44]

Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Self-citation
An improved Bonferroni procedure for multiple tests of significance
SIMES, R. J. (1986) · Biometrika · doi:10.1093/biomet/73.3.751 · Cited by 2,396

Flagged first, then by citations

Research works printed but not linked: 26

Benjamini Y, 1993, Series in Statistics 93.1, Technical Report of the Department of Statistics and OR
10.1080/01621459.1998.10474112 · DOI
Cox DR, 1965, Technometrics, 2, 149
Harvånek & Chytil, 1983, Bulletin of the International Statistical Institution, 50, l
10.1093/biomet/75.4.773 · DOI
10.1093/biomet/75.4.800 · DOI · Paper page
10.1002/sim.4780090710 · DOI · Paper page
10.1002/9780470316672 · DOI · Paper page
Holm S, 1979, Scandinavian Journal of Statistics, 6, 65
10.1093/biomet/75.2.383 · DOI
Hommel G, 1987, Multiple hypotheses testing, 154
10.1037/0033-2909.114.2.266 · DOI
10.1111/0162-895X.00104 · DOI
10.1093/biomet/69.3.493 · DOI
10.1080/00401706.1968.10490605 · DOI
10.1016/S0378-3758(99)00037-3 · DOI
10.1016/S0378-3758(99)00028-2 · DOI
10.1146/annurev.ps.46.020195.003021 · DOI · Paper page
Soriç B, 1989, Journal of the American Statistical Association, 84, 608
10.1016/S0378-3758(99)00145-7 · DOI
10.1214/ss/1177011945 · DOI · Paper page
10.1126/science.333584 · DOI
10.1055/s-0038-1635393 · DOI
Williams VSL, 1994, Technical Report #33
10.3102/10769986024001042 · DOI
10.1016/S0378-3758(99)00041-5 · DOI

Sorted by citations

The control of the false discovery rate in multiple testing under dependency
Benjamini, Y., & Yekutieli, D. (2001) · The Annals of Statistics · doi:10.1214/aos/1013699998 · Cited by 10,490
Self-citation
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692
A Direct Approach to False Discovery Rates
Storey, J. D. (2002) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00346 · Cited by 5,603
Controlling the false discovery rate in behavior genetics research
Benjamini, Y., Drai, D., Elmer, G., Kafkafi, N., & Golani, I. (2001) · Behavioural Brain Research · doi:10.1016/s0166-4328(01)00297-2 · Cited by 4,146
Self-citation
The positive false discovery rate: a Bayesian interpretation and the q-value
Storey, J. D. (2003) · The Annals of Statistics · doi:10.1214/aos/1074290335 · Cited by 2,204
Identifying differentially expressed genes using false discovery rate controlling procedures
Reiner, A., Yekutieli, D., & Benjamini, Y. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btf877 · Cited by 1,765
Self-citation
Multiple Comparisons Using R
Bretz, F., Hothorn, T., & Westfall, P. (2016) · doi:10.1201/9781420010909 · Cited by 1,233
Characterising the bacterial microbiota across the gastrointestinal tracts of dairy cattle: membership and potential function
Mao, S., Zhang, M., Liu, J., & Zhu, W. (2015) · Scientific Reports · doi:10.1038/srep16116 · Cited by 532
Effect of Continuous Glucose Monitoring on Glycemic Control in Adolescents and Young Adults With Type 1 Diabetes: A Randomized Clinical Trial
Laffel, L. M., Kanapka, L. G., Beck, R. W., Bergamo, K., Clements, M. A., Criego, A., DeSalvo, D. J., Goland, R., Hood, K., Liljenquist, D., et al. (2020) · JAMA · doi:10.1001/jama.2020.6940 · Cited by 443
Behavioral and Cognitive Characteristics of Females and Males With Autism in the Simons Simplex Collection
Frazier, T. W., Georgiades, S., Bishop, S. L., & Hardan, A. Y. (2014) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2013.12.004 · Cited by 409
Genetics of brain fiber architecture and intellectual performance
Chiang, M.-C., Barysheva, M., Shattuck, D. W., Lee, A. D., Madsen, S. K., Avedissian, C., Klunder, A. D., Toga, A. W., McMahon, K. L., de Zubicaray, G. I., et al. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.4184-08.2009 · Cited by 406
Head circumference and height in autism: A study by the collaborative program of excellence in autism
Lainhart, J. E., Bigler, E. D., Bocian, M., Coon, H., Dinh, E., Dawson, G., Deutsch, C. K., Dunn, M., Estes, A., Tager‐Flusberg, H., et al. (2006) · American Journal of Medical Genetics Part A · doi:10.1002/ajmg.a.31465 · Cited by 381
Effect of Continuous Glucose Monitoring on Hypoglycemia in Older Adults With Type 1 Diabetes: A Randomized Clinical Trial
Pratley, R. E., Kanapka, L. G., Rickels, M. R., Ahmann, A., Aleppo, G., Beck, R., Bhargava, A., Bode, B. W., Carlson, A., Chaytor, N. S., et al. (2020) · JAMA · doi:10.1001/jama.2020.6928 · Cited by 375
A comparison of two hybrid closed-loop systems in adolescents and young adults with type 1 diabetes (FLAIR): a multicentre, randomised, crossover trial
Bergenstal, R. M., Nimri, R., Beck, R. W., Criego, A., Laffel, L., Schatz, D., Battelino, T., Danne, T., Weinzimer, S. A., Sibayan, J., et al. (2021) · The Lancet · doi:10.1016/s0140-6736(20)32514-9 · Cited by 344
Long-Term Neuroinflammation Induced by Influenza A Virus Infection and the Impact on Hippocampal Neuron Morphology and Function
Hosseini, S., Wilk, E., Michaelsen-Preusse, K., Gerhauser, I., Baumgärtner, W., Geffers, R., Schughart, K., & Korte, M. (2018) · The Journal of Neuroscience · doi:10.1523/jneurosci.1740-17.2018 · Cited by 236
A step-down multiple hypotheses testing procedure that controls the false discovery rate under independence
Benjamini, Y., & Liu, W. (1999) · Journal of Statistical Planning and Inference · doi:10.1016/s0378-3758(99)00040-3 · Cited by 242
Self-citation
Clinical and neural effects of six-week administration of oxytocin on core symptoms of autism
Watanabe, T., Kuroda, M., Kuwabara, H., Aoki, Y., Iwashiro, N., Tatsunobu, N., Takao, H., Nippashi, Y., Kawakubo, Y., Kunimatsu, A., et al. (2015) · Brain · doi:10.1093/brain/awv249 · Cited by 222
Predictors and moderators of treatment response in childhood anxiety disorders: Results from the CAMS trial.
Compton, S. N., Peris, T. S., Almirall, D., Birmaher, B., Sherrill, J., Kendall, P. C., March, J. S., Gosch, E. A., Ginsburg, G. S., Rynn, M. A., et al. (2014) · Journal of Consulting and Clinical Psychology · doi:10.1037/a0035458 · Cited by 226
Multiple Hypothesis Testing to Detect Lineages under Positive Selection that Affects Only a Few Sites
Anisimova, M., & Yang, Z. (2007) · Molecular Biology and Evolution · doi:10.1093/molbev/msm042 · Cited by 213
A Preliminary Longitudinal Magnetic Resonance Imaging Study of Brain Volume and Cortical Thickness in Autism
Hardan, A. Y., Libove, R. A., Keshavan, M. S., Melhem, N. M., & Minshew, N. J. (2009) · Biological Psychiatry · doi:10.1016/j.biopsych.2009.04.024 · Cited by 173
Large-scale brain network dynamics supporting adolescent cognitive control
Dwyer, D. B., Harrison, B. J., Yücel, M., Whittle, S., Zalesky, A., Pantelis, C., Allen, N. B., & Fornito, A. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.1634-14.2014 · Cited by 143
A Clinical Trial of In-Home CBT for Depressed Mothers in Home Visitation
Ammerman, R. T., Putnam, F. W., Altaye, M., Stevens, J., Teeters, A. R., & Van Ginkel, J. B. (2013) · Behavior Therapy · doi:10.1016/j.beth.2013.01.002 · Cited by 123
Anxiogenic effects of developmental bisphenol A exposure are associated with gene expression changes in the juvenile rat amygdala and mitigated by soy
Patisaul, H. B., Sullivan, A. W., Radford, M. E., Walker, D. M., Adewale, H. B., Winnik, B., Coughlin, J. L., Buckley, B., & Gore, A. C. (2012) · PLoS ONE · doi:10.1371/journal.pone.0043890 · Cited by 106
Genome‐wide association study of alcohol use disorder identification test (AUDIT) scores in 20 328 research participants of European ancestry
Sanchez‐Roige, S., Fontanillas, P., Elson, S. L., The 23andMe Research Team, Gray, J. C., de Wit, H., Davis, L. K., MacKillop, J., & Palmer, A. A. (2019) · Addiction Biology · doi:10.1111/adb.12574 · Cited by 101
Prior physical synchrony enhances rapport and inter-brain synchronization during subsequent educational communication
Nozawa, T., Sakaki, K., Ikeda, S., Jeong, H., Yamazaki, S., Kawata, K. H. D. S., Kawata, N. Y. D. S., Sasaki, Y., Kulason, K., Hirano, K., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-49257-z · Cited by 95
Fifteen year follow-up of a randomized trial of a preventive intervention for divorced families: Effects on mental health and substance use outcomes in young adulthood
Wolchik, S. A., Sandler, I. N., Tein, J.-Y., Mahrer, N. E., Millsap, R. E., Winslow, E., Vélez, C., Porter, M. M., Luecken, L. J., & Reed, A. (2013) · Journal of Consulting and Clinical Psychology · doi:10.1037/a0033235 · Cited by 91
Relationship of white matter network topology and cognitive outcome in adolescents with d-transposition of the great arteries
Panigrahy, A., Schmithorst, V. J., Wisnowski, J. L., Watson, C. G., Bellinger, D. C., Newburger, J. W., & Rivkin, M. J. (2015) · NeuroImage: Clinical · doi:10.1016/j.nicl.2015.01.013 · Cited by 86
Plasma and urinary metabolomic profiles of Down syndrome correlate with alteration of mitochondrial metabolism
Caracausi, M., Ghini, V., Locatelli, C., Mericio, M., Piovesan, A., Antonaros, F., Pelleri, M. C., Vitale, L., Vacca, R. A., Bedetti, F., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-20834-y · Cited by 84
Metabolic Networks and Metabolites Underlie Associations Between Maternal Glucose During Pregnancy and Newborn Size at Birth.
Scholtens, D. M., Bain, J. R., Reisetter, A. C., Muehlbauer, M. J., Nodzenski, M., Stevens, R. D., Ilkayeva, O., Lowe, L. P., Metzger, B. E., Newgard, C. B., et al. (2016) · Diabetes · doi:10.2337/db15-1748 · Cited by 69
Dynamic Postnatal Developmental and Sex-Specific Neuroendocrine Effects of Prenatal Polychlorinated Biphenyls in rats
Walker, D. M., Goetz, B. M., & Gore, A. C. (2014) · Molecular Endocrinology · doi:10.1210/me.2013-1270 · Cited by 73
Benefit of Continuous Glucose Monitoring in Reducing Hypoglycemia Is Sustained Through 12 Months of Use Among Older Adults with Type 1 Diabetes
Miller, K. M., Kanapka, L. G., Rickels, M. R., Ahmann, A. J., Aleppo, G., Ang, L., Bhargava, A., Bode, B. W., Carlson, A., Chaytor, N. S., et al. (2022) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2021.0503 · Cited by 73
Disuse deterioration of human skeletal muscle challenged by resistive exercise superimposed with vibration: evidence from structural and proteomic analysis
Salanova, M., Gelfi, C., Moriggi, M., Vasso, M., Viganò, A., Minafra, L., Bonifacio, G., Schiffl, G., Gutsmann, M., Felsenberg, D., et al. (2014) · The FASEB Journal · doi:10.1096/fj.14-252825 · Cited by 68
Three major dimensions of human brain cortical ageing in relation to cognitive decline across the eighth decade of life
Cox, S. R., Harris, M. A., Ritchie, S. J., Buchanan, C. R., Valdés Hernández, M. C., Corley, J., Taylor, A. M., Madole, J. W., Harris, S. E., Whalley, H. C., et al. (2021) · Molecular Psychiatry · doi:10.1038/s41380-020-00975-1 · Cited by 60
A transcriptome-wide association study based on 27 tissues identifies 106 genes potentially relevant for disease pathology in age-related macular degeneration
Strunz, T., Lauwen, S., Kiel, C., International AMD Genomics Consortium (IAMDGC), Fritsche, L. G., Igl, W., Bailey, J. N. C., Grassmann, F., Sengupta, S., Bragg-Gresham, J. L., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-58510-9 · Cited by 60
Prenatal cocaine effects on brain structure in early infancy
Grewen, K., Burchinal, M., Vachet, C., Gouttard, S., Gilmore, J. H., Lin, W., Johns, J., Elam, M., & Gerig, G. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.06.070 · Cited by 65
Subjective Loudness and Reality of Auditory Verbal Hallucinations and Activation of the Inner Speech Processing Network
Vercammen, A., Knegtering, H., Bruggeman, R., & Aleman, A. (2011) · Schizophrenia Bulletin · doi:10.1093/schbul/sbq007 · Cited by 63
Functional brain connectivity in ex utero premature infants compared to in utero fetuses
De Asis-Cruz, J., Kapse, K., Basu, S. K., Said, M., Scheinost, D., Murnick, J., Chang, T., du Plessis, A., & Limperopoulos, C. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117043 · Cited by 63
Associations Between Resting-State Functional Connectivity and a Hierarchical Dimensional Structure of Psychopathology in Middle Childhood
Karcher, N. R., Michelini, G., Kotov, R., & Barch, D. M. (2021) · Biological Psychiatry: Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2020.09.008 · Cited by 55
Positive impact of the bionic pancreas on diabetes control in youth 6-17 years old with type 1 diabetes: a multicenter randomized trial
Bionic Pancreas Research Group, Messer, L. H., Buckingham, B. A., Cogen, F., Daniels, M., Forlenza, G., Jafri, R. Z., Mauras, N., Muir, A., Wadwa, R. P., et al. (2022) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2022.0201.pub · Cited by 59
Early adverse life events are associated with altered brain network architecture in a sex- dependent manner
Gupta, A., Mayer, E. A., Acosta, J. R., Hamadani, K., Torgerson, C., van Horn, J. D., Chang, L., Naliboff, B., Tillisch, K., & Labus, J. S. (2017) · Neurobiology of Stress · doi:10.1016/j.ynstr.2017.02.003 · Cited by 56
Hyperconnectivity of the right posterior temporo-parietal junction predicts social difficulties in boys with autism spectrum disorder
Chien, H., Lin, H., Lai, M., Gau, S. S., & Tseng, W. I. (2015) · Autism Research · doi:10.1002/aur.1457 · Cited by 54
Morphological brain measures of cortico‐limbic inhibition related to resilience
Gupta, A., Love, A., Kilpatrick, L. A., Labus, J. S., Bhatt, R., Chang, L., Tillisch, K., Naliboff, B., & Mayer, E. A. (2017) · Journal of Neuroscience Research · doi:10.1002/jnr.24007 · Cited by 54
A modified Benjamini–Hochberg multiple comparisons procedure for controlling the false discovery rate
Kwong, K. S., Holland, B., & Cheung, S. H. (2002) · Journal of Statistical Planning and Inference · doi:10.1016/s0378-3758(01)00252-x · Cited by 54
A multicenter randomized trial evaluating fast-acting insulin aspart in the bionic pancreas in adults with type 1 diabetes
Bionic Pancreas Research Group, Beck, R. W., Russell, S. J., Damiano, E. R., El-Khatib, F. H., Ruedy, K. J., Balliro, C., Li, Z., & Calhoun, P. (2022) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2022.0167 · Cited by 40
A multicenter randomized trial evaluating the insulin-only configuration of the bionic pancreas in adults with type 1 diabetes
Bionic Pancreas Research Group, Kruger, D., Kass, A., Lonier, J., Pettus, J., Raskin, P., Salam, M., Trikudanathan, S., Zhou, K., Russell, S. J., et al. (2022) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2022.0200 · Cited by 38
Beneficial effects of Control-IQ automated insulin delivery in basal-bolus and basal-only insulin users with type 2 diabetes
Levy, C. J., Raghinaru, D., Kudva, Y. C., Pandit, K., Blevins, T., Casaubon, L., Desjardins, D., Levister, C. M., O’Malley, G., Reid, C., et al. (2024) · Clinical Diabetes · doi:10.2337/cd23-0025 · Cited by 37
Intermittent Fasting Implementation and Association with Eating Disorder Symptomatology
Cuccolo, K., Kramer, R., Petros, T., & Thoennes, M. (2022) · Eating Disorders · doi:10.1080/10640266.2021.1922145 · Cited by 33
Mindfulness, Obsessive–Compulsive Symptoms, and Executive Dysfunction
Crowe, K., & McKay, D. (2016) · Cognitive Therapy and Research · doi:10.1007/s10608-016-9777-x · Cited by 32
Amyloid-beta induced retrograde axonal degeneration in a mouse tauopathy model
Nishioka, C., Liang, H.-F., Barsamian, B., & Sun, S.-W. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.01.007 · Cited by 30
Implicit Cognitions as a Behavioral Marker of Suicide Attempts in Adolescents
Millner, A. J., Augenstein, T. M., Visser, K. H., Gallagher, K., Vergara, G. A., D’Angelo, E. J., & Nock, M. K. (2019) · Archives of Suicide Research · doi:10.1080/13811118.2017.1421488 · Cited by 29
Prediction of English and Spanish kindergarten mathematics from English and Spanish cognitive and linguistic abilities in Hispanic dual language learners
Foster, M. E., Anthony, J. L., Zucker, T. A., & Branum-Martin, L. (2019) · Early Childhood Research Quarterly · doi:10.1016/j.ecresq.2018.02.007 · Cited by 26
Attention-Deficit/Hyperactivity Disorder (ADHD) and Motor Timing in Adolescents and Their Parents: Familial Characteristics of Reaction Time Variability Vary With Age
Thissen, A. J. A. M., Luman, M., Hartman, C., Hoekstra, P., van Lieshout, M., Franke, B., Oosterlaan, J., Rommelse, N. N. J., & Buitelaar, J. K. (2014) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2014.05.015 · Cited by 22
Long-term continuous glucose monitor use in very young children with type 1 diabetes: one-year results from the SENCE study
Van Name, M. A., Kanapka, L. G., DiMeglio, L. A., Miller, K. M., Albanese-O’Neill, A., Commissariat, P., Corathers, S. D., Harrington, K. R., Hilliard, M. E., Anderson, B. J., et al. (2023) · Journal of Diabetes Science and Technology · doi:10.1177/19322968221084667 · Cited by 20
Rapid anti-myeloma activity by T cells expressing an anti-BCMA CAR with a human heavy-chain-only antigen-binding domain
Mikkilineni, L., Natrakul, D. A., Lam, N., Manasanch, E. E., Mann, J., Weissler, K. A., Wong, N., Brudno, J. N., Goff, S. L., Yang, J. C., et al. (2024) · Molecular Therapy · doi:10.1016/j.ymthe.2023.12.018 · Cited by 16
Chebyshev’s Inequality for Nonparametric Testing with Small N and α in Microarray Research
Beasley, T. M., Page, G. P., Brand, J. P. L., Gadbury, G. L., Mountz, J. D., & Allison, D. B. (2004) · Journal of the Royal Statistical Society Series C: Applied Statistics · doi:10.1111/j.1467-9876.2004.00428.x · Cited by 15
Integrative Data Analysis and the Study of Global Health
Hussong, A. M., Cole, V. T., Curran, P. J., Bauer, D. J., & Gottfredson, N. C. (2020) · ICSA Book Series in Statistics · doi:10.1007/978-3-030-35260-8_5 · Cited by 13
Child anxiety prevention study: impact on functional outcomes
Pella, J. E., Drake, K. L., Tein, J.-Y., & Ginsburg, G. S. (2017) · Child Psychiatry & Human Development · doi:10.1007/s10578-016-0667-y · Cited by 12
Systematic analysis of the effects of splicing on the diversity of post-translational modifications in protein isoforms using PTM-POSE
Crowl, S., Coleman, M. B., Chaphiv, A., Jordan, B. T., & Naegle, K. M. (2025) · Cell Systems · doi:10.1016/j.cels.2025.101318 · Cited by 10
Allergic tendencies are associated with larger gray matter volumes
Takeuchi, H., Taki, Y., Nouchi, R., Yokoyama, R., Kotozaki, Y., Nakagawa, S., Sekiguchi, A., Iizuka, K., Yamamoto, Y., Hanawa, S., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-21985-8 · Cited by 8
Early-life adversity severity, timing, and context type are associated with SLC6A4 methylation in emerging adults: results from a prospective cohort study
Koning, S. M., Kessler, C. L., Canli, T., Duman, E. A., Adam, E. K., Zinbarg, R., Craske, M. G., Stephens, J. E., & Vrshek-Schallhorn, S. (2024) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2024.107181 · Cited by 8
Assessing peri-implant bacterial community structure: the effect of microbiome sample collection method
Anitua, E., Murias-Freijo, A., Tierno, R., Tejero, R., & Alkhraisat, M. H. (2024) · BMC Oral Health · doi:10.1186/s12903-024-04675-y · Cited by 7
Association of physical function with connectivity in the sensorimotor and dorsal attention networks: Why examining specific components of physical function matters
Boyd, M. C., Burdette, J. H., Miller, M. E., Lyday, R. G., Hugenschmidt, C. E., Jack Rejeski, W., Simpson, S. L., Baker, L. D., Tomlinson, C. E., Kritchevsky, S. B., et al. (2024) · GeroScience · doi:10.1007/s11357-024-01251-8 · Cited by 3
Cell signaling pathways discovery from multi-modal data
He, C., Simpson, C., Cossentino, I., Zhang, B., Tkachev, S., Eddins, D. J., Kosters, A., Yang, J., Sheth, S., Levy, T., et al. (2025) · doi:10.1101/2025.02.06.636961 · Cited by 3
Shared and distinct microRNA profiles between HT22, N2A and SH-SY5Y cell lines and primary mouse hippocampal neurons
Murphy, R., Villegas-Salmerón, J., Sanz-Rodriguez, A., Engel, T., Mooney, C., Henshall, D. C., & Jimenez-Mateos, E. M. (2025) · PLOS One · doi:10.1371/journal.pone.0326401 · Cited by 3
Investigating an Acceptance and Commitment Therapy-Based Exposure Therapy Intervention in Treatment-Refractory OCD and Related Disorders: Changes in Psychological Flexibility, Treatment Engagement, and Treatment Perceptions.
Gruner, N. G., Cullen, J. M., Crosby, J. M., DeCross, S. N., Mathes, B., Garner, L., Gironda, C., Hu, Y., Krompinger, J. W., Elias, J. A., et al. (2024) · Journal of Cognitive Psychotherapy · doi:10.1891/jcp-2022-0033

Authors: Benjamini, Y., & Hochberg, Y.
Affiliations: Tel Aviv University (IL)
ORCID: Benjamini, Yoav
Venue: Journal of Educational and Behavioral Statistics
Publisher: American Educational Research Association (AERA)
Published: 2000-03
Volume: 25
Issue: 1
Pages: 60-83
ISSN: 1076-9986 (ISSN-L)
1935-1054
DOI: 10.3102/10769986025001060
OpenAlex: W2143079975
Cited by: 2,015
References: 2
Citations by year: 2026: 88 · 2025: 141 · 2024: 146 · 2023: 136 · 2022: 118 · 2021: 134 · 2020: 134 · 2019: 125 · 2018: 102 · 2017: 83 · 2016: 94 · 2015: 85 · 2014: 94 · 2013: 81 · 2012: 51
FWCI: 10.54
Type: journal article
Language: en
Open access: closed
Licence: journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations: Journal of Educational and Behavioral Statistics (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Keywords: false discovery rate, multiple comparisons, adaptive procedures, Benjamini-Hochberg procedure, stepwise procedures, statistical power, family-wise error rate, multicenter study, subgroup analysis, meta-analysis

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.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

On the Adaptive Control of the False Discovery Rate in Multiple Testing With Independent Statistics

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Metadata

Record

About these checks