Modern Applied Statistics with S

Support-vector networks

Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421

The Nature of Statistical Learning Theory

Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138

The Elements of Statistical Learning

Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162

Multilayer feedforward networks are universal approximators

Hornik, K., Stinchcombe, M., & White, H. (1989) · Neural Networks · doi:10.1016/0893-6080(89)90020-8 · Cited by 21,728

Finite Mixture Models

McLachlan, G., & Peel, D. (2000) · Wiley Series in Probability and Statistics · doi:10.1002/0471721182 · Cited by 10,991

Mixed-Effects Models in S and S-PLUS

(2001) · Technometrics · doi:10.1198/tech.2001.s574 · Cited by 9,278

A note on a general definition of the coefficient of determination

NAGELKERKE, N. J. D. (1991) · Biometrika · doi:10.1093/biomet/78.3.691 · Cited by 5,927

On a Least Squares Adjustment of a Sampled Frequency Table When the Expected Marginal Totals are Known

Deming, W. E., & Stephan, F. F. (1940) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177731829 · Cited by 1,537

A practical data processing workflow for multi-OMICS projects

Kohl, M., Megger, D. A., Trippler, M., Meckel, H., Ahrens, M., Bracht, T., Weber, F., Hoffmann, A.-C., Baba, H. A., Sitek, B., et al. (2014) · Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics · doi:10.1016/j.bbapap.2013.02.029 · Cited by 60

Dose–response Relationship of Reported Lifetime Meditation Practice with Mental Health and Wellbeing: a Cross-sectional Study

Bowles, N. I., Davies, J. N., & Van Dam, N. T. (2022) · Mindfulness · doi:10.1007/s12671-022-01977-6 · Cited by 58

Associations between Child Maltreatment, Harsh Parenting, and Sleep with Adolescent Mental Health

Calhoun, B. H., Ridenour, T. A., & Fishbein, D. H. (2019) · Journal of Child and Family Studies · doi:10.1007/s10826-018-1261-7 · Cited by 56

Longitudinal processing speed impairments in males with autism and the effects of white matter microstructure

Travers, B. G., Bigler, E. D., Tromp, D. P. M., Adluru, N., Froehlich, A. L., Ennis, C., Lange, N., Nielsen, J. A., Prigge, M. B. D., Alexander, A. L., et al. (2014) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2013.11.008 · Cited by 58

Soil and microbial properties of green infrastructure stormwater management systems

Deeb, M., Groffman, P. M., Joyner, J. L., Lozefski, G., Paltseva, A., Lin, B., Mania, K., Cao, D. L., McLaughlin, J., Muth, T., et al. (2018) · Ecological Engineering · doi:10.1016/j.ecoleng.2018.10.017 · Cited by 57

Smoking Cessation Smartphone App Use Over Time: Predicting 12-Month Cessation Outcomes in a 2-Arm Randomized Trial

Bricker, J. B., Mull, K. E., Santiago-Torres, M., Miao, Z., Perski, O., & Di, C. (2022) · Journal of Medical Internet Research · doi:10.2196/39208 · Cited by 44

Measuring the stability of results from supervised statistical learning

Philipp, M., Rusch, T., Hornik, K., & Strobl, C. (2018) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.2018.1473779 · Cited by 56

Spatial and temporal patterns of surface water quality and ichthyotoxicity in urban and rural river basins in Texas

VanLandeghem, M. M., Meyer, M. D., Cox, S. B., Sharma, B., & Patiño, R. (2012) · Water Research · doi:10.1016/j.watres.2012.05.002 · Cited by 56

A house with a view? multi-model inference, visibility fields, and point process analysis of a Bronze age settlement on Leskernick Hill (Cornwall, UK)

Eve, S. J., & Crema, E. R. (2014) · Journal of Archaeological Science · doi:10.1016/j.jas.2013.12.019 · Cited by 55

Striatal hyposensitivity to delayed rewards among cigarette smokers

Luo, S., Ainslie, G., Giragosian, L., & Monterosso, J. R. (2011) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2010.11.012 · Cited by 52

A supervised machine-learning approach towards geochemical predictive modelling in archaeology

Oonk, S., & Spijker, J. (2015) · Journal of Archaeological Science · doi:10.1016/j.jas.2015.04.002 · Cited by 53

Using Administrative Data to Predict Suicide After Psychiatric Hospitalization in the Veterans Health Administration System

Kessler, R. C., Bauer, M. S., Bishop, T. M., Demler, O. V., Dobscha, S. K., Gildea, S. M., Goulet, J. L., Karras, E., Kreyenbuhl, J., Landes, S. J., et al. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.00390 · Cited by 52

Ecotoxicology is not normal: A comparison of statistical approaches for analysis of count and proportion data in ecotoxicology

Szöcs, E., & Schäfer, R. B. (2015) · Environmental Science and Pollution Research · doi:10.1007/s11356-015-4579-3 · Cited by 52

Variation in wild pea (Pisum sativum subsp.elatius) seed dormancy and its relationship to the environment and seed coat traits

Hradilová, I., Duchoslav, M., Brus, J., Pechanec, V., Hýbl, M., Kopecký, P., Smržová, L., Štefelová, N., Vaclávek, T., Bariotakis, M., et al. (2019) · PeerJ · doi:10.7717/peerj.6263 · Cited by 52

Variational Bayes approximations for clustering via mixtures of normal inverse Gaussian distributions

Subedi, S., & McNicholas, P. D. (2014) · Advances in Data Analysis and Classification · doi:10.1007/s11634-014-0165-7 · Cited by 51

Vocal behavior of black‐fronted titi monkeys (Callicebus nigrifrons): Acoustic properties and behavioral contexts of loud calls

Caselli, C. B., Mennill, D. J., Bicca‐Marques, J. C., & Setz, E. Z. F. (2014) · American Journal of Primatology · doi:10.1002/ajp.22270 · Cited by 51

The value of necropsy reports for animal health surveillance

Küker, S., Faverjon, C., Furrer, L., Berezowski, J., Posthaus, H., Rinaldi, F., & Vial, F. (2018) · BMC Veterinary Research · doi:10.1186/s12917-018-1505-1 · Cited by 51

A smartphone app designed to help cancer patients stop smoking: results from a pilot randomized trial on feasibility, acceptability, and effectiveness

Bricker, J. B., Watson, N. L., Heffner, J. L., Sullivan, B., Mull, K., Kwon, D., Westmaas, J. L., & Ostroff, J. (2020) · JMIR Formative Research · doi:10.2196/16652 · Cited by 41

Effect of a prebiotic mixture on intestinal comfort and general wellbeing in health

Goetze, O., Fruehauf, H., Pohl, D., Giarrè, M., Rochat, F., Ornstein, K., Menne, D., Fried, M., & Thumshirn, M. (2008) · British Journal of Nutrition · doi:10.1017/s0007114508960918 · Cited by 49

Using machine learning to disentangle homonyms in large text corpora

Roll, U., Correia, R. A., & Berger‐Tal, O. (2018) · Conservation Biology · doi:10.1111/cobi.13044 · Cited by 46

Dinosaur biogeographical structure and Mesozoic continental fragmentation: a network‐based approach

Dunhill, A. M., Bestwick, J., Narey, H., & Sciberras, J. (2016) · Journal of Biogeography · doi:10.1111/jbi.12766 · Cited by 47

Information content and acoustic structure of male African elephant social rumbles

Stoeger, A. S., & Baotic, A. (2016) · Scientific Reports · doi:10.1038/srep27585 · Cited by 47

Benefits of training/playing therapy in a group of captive lowland gorillas (Gorilla gorilla gorilla)

Carrasco, L., Colell, M., Calvo, M., Abelló, M., Velasco, M., & Posada, S. (2009) · Animal Welfare · doi:10.1017/s0962728600000026 · Cited by 46

Parp mutations protect from mitochondrial toxicity in Alzheimer’s disease

Yu, Y., Fedele, G., Celardo, I., Loh, S. H. Y., & Martins, L. M. (2021) · Cell Death & Disease · doi:10.1038/s41419-021-03926-y · Cited by 46

What counts as evidence for working memory training? Problems with correlated gains and dichotomization

Tidwell, J. W., Dougherty, M. R., Chrabaszcz, J. R., Thomas, R. P., & Mendoza, J. L. (2014) · Psychonomic Bulletin & Review · doi:10.3758/s13423-013-0560-7 · Cited by 45

Plasticity in vertical behaviour of migrating juvenile southern bluefin tuna (Thunnus maccoyii) in relation to oceanography of the south Indian Ocean

BESTLEY, S., GUNN, J. S., & HINDELL, M. A. (2009) · Fisheries Oceanography · doi:10.1111/j.1365-2419.2009.00509.x · Cited by 45

Application of a semi-automated vocal fingerprinting approach to monitor Bornean gibbon females in an experimentally fragmented landscape in Sabah, Malaysia

Clink, D. J., Crofoot, M. C., & Marshall, A. J. (2019) · Bioacoustics · doi:10.1080/09524622.2018.1426042 · Cited by 44

Untangling genotype x management interactions in multi-environment on-farm experimentation

Rotili, D. H., de Voil, P., Eyre, J., Serafin, L., Aisthorpe, D., Maddonni, G. Á., & Rodríguez, D. (2020) · Field Crops Research · doi:10.1016/j.fcr.2020.107900 · Cited by 44

Detecting cracks in aircraft engine fan blades using vibrothermography nondestructive evaluation

Gao, C., Meeker, W. Q., & Mayton, D. (2014) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2014.05.009 · Cited by 44

The relation between classroom management and mathematics achievement: A multilevel structural equation model

van Dijk, W., Gage, N. A., & Grasley‐Boy, N. (2019) · Psychology in the Schools · doi:10.1002/pits.22254 · Cited by 44

Positive Feedbacks to Fire-Driven Deforestation Following Human Colonization of the South Island of New Zealand

Tepley, A. J., Veblen, T. T., Perry, G. L. W., Stewart, G. H., & Naficy, C. E. (2016) · Ecosystems · doi:10.1007/s10021-016-0008-9 · Cited by 44

Genome-wide association study and scan for signatures of selection point to candidate genes for body temperature maintenance under the cold stress in Siberian cattle populations

Igoshin, A. V., Yurchenko, A. A., Belonogova, N. M., Petrovsky, D. V., Aitnazarov, R. B., Soloshenko, V. A., Yudin, N. S., & Larkin, D. M. (2019) · BMC Genetics · doi:10.1186/s12863-019-0725-0 · Cited by 42

Encoding of reward expectation by monkey anterior insular neurons

Mizuhiki, T., Richmond, B. J., & Shidara, M. (2012) · Journal of Neurophysiology · doi:10.1152/jn.00282.2011 · Cited by 41

Longitudinal Assessment of Amyloid Pathology in Transgenic ArcAβ Mice Using Multi-Parametric Magnetic Resonance Imaging

Klohs, J., Politano, I. W., Deistung, A., Grandjean, J., Drewek, A., Dominietto, M., Keist, R., Schweser, F., Reichenbach, J. R., Nitsch, R. M., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0066097 · Cited by 42

CiwGAN and fiwGAN: Encoding information in acoustic data to model lexical learning with Generative Adversarial Networks

Beguš, G. (2021) · Neural Networks · doi:10.1016/j.neunet.2021.03.017 · Cited by 42

Long‐Term Biomass Yield and Species Composition in Native Perennial Bioenergy Cropping Systems

Jungers, J. M., Clark, A. T., Betts, K., Mangan, M. E., Sheaffer, C. C., & Wyse, D. L. (2015) · Agronomy Journal · doi:10.2134/agronj15.0014 · Cited by 39

Pilot Randomized Controlled Trial of Web-Delivered Acceptance and Commitment Therapy Versus Smokefree.gov for Smokers With Bipolar Disorder

Heffner, J. L., Kelly, M. M., Waxmonsky, J., Mattocks, K., Serfozo, E., Bricker, J. B., Mull, K. E., Watson, N. L., & Ostacher, M. (2020) · Nicotine & Tobacco Research · doi:10.1093/ntr/ntz242 · Cited by 39

Amendment of degraded desert soil with wastewater debris containing immobilized Chlorella sorokiniana and Azospirillum brasilense significantly modifies soil bacterial community structure, diversity, and richness

Lopez, B. R., Bashan, Y., Trejo, A., & de-Bashan, L. E. (2013) · Biology and Fertility of Soils · doi:10.1007/s00374-013-0799-1 · Cited by 38

Comparing evolutionary rates between trees, clades and traits

Revell, L. J., González‐Valenzuela, L. E., Alfonso, A., Castellanos‐García, L. A., Guarnizo, C. E., & Crawford, A. J. (2018) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.12977 · Cited by 38

Landscape Archaeology between Art and Science: From a Multi- to an Interdisciplinary Approach

(2012) · doi:10.1515/9789048516070 · Cited by 37

A retrotransposon storm marks clinical phenoconversion to late-onset Alzheimer’s disease

Macciardi, F., Giulia Bacalini, M., Miramontes, R., Boattini, A., Taccioli, C., Modenini, G., Malhas, R., Anderlucci, L., Gusev, Y., Gross, T. J., et al. (2022) · GeroScience · doi:10.1007/s11357-022-00580-w · Cited by 37

Why do volunteer content moderators quit? Burnout, conflict, and harmful behaviors

Schöpke-Gonzalez, A. M., Atreja, S., Shin, H. N., Ahmed, N., & Hemphill, L. (2024) · New Media & Society · doi:10.1177/14614448221138529 · Cited by 37

Understanding the effectiveness of automated feedback: Using process data to uncover the role of behavioral engagement

Schiller, R., Fleckenstein, J., Mertens, U., Horbach, A., & Meyer, J. (2024) · Computers & Education · doi:10.1016/j.compedu.2024.105163 · Cited by 36

Intensive Human Contact Correlates with Smaller Brains: Differential Brain Size Reduction in Cattle Types

Balcarcel, A. M., Veitschegger, K., Clauss, M., & Sánchez-Villagra, M. R. (2021) · Proceedings of the Royal Society B: Biological Sciences · doi:10.1098/rspb.2021.0813 · Cited by 35

Sensitivity of typical European roadside plants to atmospheric particulate matter

Kováts, N., Hubai, K., Diósi, D., Sainnokhoi, T.-A., Hoffer, A., Tóth, Á., & Teke, G. (2021) · Ecological Indicators · doi:10.1016/j.ecolind.2021.107428 · Cited by 34

Anorexia Nervosa, Autism, and the ADOS: How Appropriate Is the New Algorithm in Identifying Cases?

Sedgewick, F., Kerr-Gaffney, J., Leppanen, J., & Tchanturia, K. (2019) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2019.00507 · Cited by 34

Myosin7a Deficiency Results in Reduced Retinal Activity Which Is Improved by Gene Therapy

Colella, P., Sommella, A., Marrocco, E., Di Vicino, U., Polishchuk, E., Garrido, M. G., Seeliger, M. W., Polishchuk, R., & Auricchio, A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0072027 · Cited by 34

Rule reversal: ecogeographical patterns of body size variation in the common treeshrew (Mammalia, Scandentia)

Sargis, E. J., Millien, V., Woodman, N., & Olson, L. E. (2018) · Ecology and Evolution · doi:10.1002/ece3.3682 · Cited by 32

Spatial machine-learning model diagnostics: a model-agnostic distance-based approach

Brenning, A. (2023) · International Journal of Geographical Information Science · doi:10.1080/13658816.2022.2131789 · Cited by 33

Assessment of growth phases of the diatom Ditylum brightwellii by FT-IR and Raman spectroscopy

Rüger, J., Unger, N., Schie, I. W., Brunner, E., Popp, J., & Krafft, C. (2016) · Algal Research · doi:10.1016/j.algal.2016.09.007 · Cited by 32

Epigenome‐wide analysis uncovers a blood‐based DNA methylation biomarker of lifetime cannabis use

Markunas, C. A., Hancock, D. B., Xu, Z., Quach, B. C., Fang, F., Sandler, D. P., Johnson, E. O., & Taylor, J. A. (2021) · American Journal of Medical Genetics Part B: Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32813 · Cited by 31

The dynamics of adaptation to stress from standing genetic variation and de novo mutations

Ament-Velásquez, S. L., Gilchrist, C., Rêgo, A., Bendixsen, D. P., Brice, C., Grosse-Sommer, J. M., Rafati, N., & Stelkens, R. (2022) · Molecular Biology and Evolution · doi:10.1093/molbev/msac242 · Cited by 31

Effects of Water Quality and Post-Harvest Handling on Microbiological Contamination of Lettuce at Urban and Peri-Urban Locations of Ouagadougou, Burkina Faso

Dao, J., Stenchly, K., Traoré, O., Amoah, P., & Buerkert, A. (2018) · Foods · doi:10.3390/foods7120206 · Cited by 31

Predictors of personal exposure to black carbon among women in southern semi-rural Mozambique

Curto, A., Donaire-Gonzalez, D., Manaca, M. N., González, R., Sacoor, C., Rivas, I., Gascon, M., Wellenius, G. A., Querol, X., Sunyer, J., et al. (2019) · Environment International · doi:10.1016/j.envint.2019.104962 · Cited by 31

Mechanisms of Smartphone Apps for Cigarette Smoking Cessation: Results of a Serial Mediation Model From the iCanQuit Randomized Trial

Bricker, J. B., Levin, M., Lappalainen, R., Mull, K., Sullivan, B., & Santiago-Torres, M. (2021) · JMIR mHealth and uHealth · doi:10.2196/32847 · Cited by 28

Longitudinal population subgroups of CRP and risk of depression in the ALSPAC birth cohort

Osimo, E. F., Stochl, J., Zammit, S., Lewis, G., Jones, P. B., & Khandaker, G. M. (2020) · Comprehensive Psychiatry · doi:10.1016/j.comppsych.2019.152143 · Cited by 30

Investigating relationships between albacore tuna (Thunnus alalunga) CPUE and prey distribution in the Bay of Biscay

Lezama-Ochoa, A., Boyra, G., Goñi, N., Arrizabalaga, H., & Bertrand, A. (2010) · Progress in Oceanography · doi:10.1016/j.pocean.2010.04.006 · Cited by 30

Trends in oyster populations in the northeastern Gulf of Mexico: an assessment of river discharge and fishing effects over time and space

Moore, J. F., Pine, W. E., Frederick, P. C., Beck, S., Moreno, M., Dodrill, M. J., Boone, M., Sturmer, L., & Yurek, S. (2020) · Marine and Coastal Fisheries · doi:10.1002/mcf2.10117 · Cited by 29

The acceptability of contraception task-sharing among pharmacists in Canada — the ACT-Pharm study

Norman, W. V., Soon, J. A., Panagiotoglou, D., Albert, A., & Zed, P. J. (2015) · Contraception · doi:10.1016/j.contraception.2015.03.013 · Cited by 28

Genetic analysis of male Hungarian Conquerors: European and Asian paternal lineages of the conquering Hungarian tribes

Fóthi, E., Gonzalez, A., Fehér, T., Gugora, A., Fóthi, Á., Biró, O., & Keyser, C. (2020) · Archaeological and Anthropological Sciences · doi:10.1007/s12520-019-00996-0 · Cited by 27

Broadly reactive human CD4 + T cells against Enterobacteriaceae are found in the naïve repertoire and are clonally expanded in the memory repertoire

Cassotta, A., Goldstein, J. D., Durini, G., Jarrossay, D., Baggi Menozzi, F., Venditti, M., Russo, A., Falcone, M., Lanzavecchia, A., Gagliardi, M. C., et al. (2021) · European Journal of Immunology · doi:10.1002/eji.202048630 · Cited by 23

Clinical outcomes of submicroscopic infections and correlates of protection of VAR2CSA antibodies in a longitudinal study of pregnant women in Colombia

Gavina, K., Gnidehou, S., Arango, E., Hamel-Martineau, C., Mitran, C., Agudelo, O., Lopez, C., Karidio, A., Banman, S., Carmona-Fonseca, J., et al. (2018) · Infection and Immunity · doi:10.1128/iai.00797-17 · Cited by 26

Blood parameters of young calves at abattoirs are related to distance transported and farm of origin

Roadknight, N., Mansell, P., Jongman, E., Courtman, N., McGill, D., Hepworth, G., & Fisher, A. (2021) · Journal of Dairy Science · doi:10.3168/jds.2020-19729 · Cited by 26

A Double Robust Approach to Causal Effects in Case-Control Studies

Rose, S., & van der Laan, M. (2014) · American Journal of Epidemiology · doi:10.1093/aje/kwt318 · Cited by 26

Using Machine Learning to Measure Relatedness Between Genes: A Multi-Features Model

Wang, Y., Yang, S., Zhao, J., Du, W., Liang, Y., Wang, C., Zhou, F., Tian, Y., & Ma, Q. (2019) · Scientific Reports · doi:10.1038/s41598-019-40780-7 · Cited by 26

Can a Single Variable Predict Early Dropout From Digital Health Interventions? Comparison of Predictive Models From Two Large Randomized Trials

Bricker, J., Miao, Z., Mull, K., Santiago-Torres, M., & Vock, D. M. (2023) · Journal of Medical Internet Research · doi:10.2196/43629 · Cited by 22

Where Wolves Kill Moose: The Influence of Prey Life History Dynamics on the Landscape Ecology of Predation

Montgomery, R. A., Vucetich, J. A., Roloff, G. J., Bump, J. K., & Peterson, R. O. (2014) · PLoS ONE · doi:10.1371/journal.pone.0091414 · Cited by 25

Motor Capacities in Boys with High Functioning Autism: Which Evaluations to Choose?

BRICOUT, V.-A., PACE, M., DUMORTIER, L., MIGANEH, S., MAHISTRE, Y., & GUINOT, M. (2019) · Journal of Clinical Medicine · doi:10.3390/jcm8101521 · Cited by 23

Influence of oceanographic variability on recruitment of yellowfin tuna (Thunnus albacares) in the western and central Pacific Ocean

Langley, A., Briand, K., Kirby, D. S., & Murtugudde, R. (2009) · Canadian Journal of Fisheries and Aquatic Sciences · doi:10.1139/f09-096 · Cited by 23

A study of the Bodrogköz population in north-eastern Hungary by Y chromosomal haplotypes and haplogroups

Pamjav, H., Fóthi, Á., Fehér, T., & Fóthi, E. (2017) · Molecular Genetics and Genomics · doi:10.1007/s00438-017-1319-z · Cited by 23

Probabilistic classifiers with high-dimensional data

Kim, K. I., & Simon, R. (2011) · Biostatistics · doi:10.1093/biostatistics/kxq069 · Cited by 23

Effects of urbanisation, habitat characteristics, and management on garden pond biodiversity: Findings from a large-scale citizen science survey

MÁRTON, Z., BARTA, B., VAD, C. F., SZABÓ, B., HAMER, A. J., KARDOS, V., LASKAI, C., FIERPASZ, Á., & HORVÁTH, Z. (2025) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2025.105299 · Cited by 22

Estimating the Milky Way's Mass via Hierarchical Bayes: A Blind Test on MUGS2 Simulated Galaxies

Eadie, G., Keller, B., & Harris, W. E. (2018) · The Astrophysical Journal · doi:10.3847/1538-4357/aadb95 · Cited by 20

A meta-analysis of pre-pregnancy maternal body mass index and placental DNA methylation identifies 27 CpG sites with implications for mother-child health

Fernandez-Jimenez, N., Fore, R., Cilleros-Portet, A., Lepeule, J., Perron, P., Kvist, T., Tian, F.-Y., Lesseur, C., Binder, A. M., Lozano, M., et al. (2022) · Communications Biology · doi:10.1038/s42003-022-04267-y · Cited by 20

Genetic architecture of plasma Alzheimer disease biomarkers

Bradley, J., Gorijala, P., Schindler, S. E., Sung, Y. J., Ances, B., the Alzheimer’s Disease Neuroimaging Initiative, T. H. C. P., Ertekin-Taner, N., Younkin, S., Golde, T., Price, N., et al. (2023) · Human Molecular Genetics · doi:10.1093/hmg/ddad087 · Cited by 20

ChatGPT as a Tool for Biostatisticians: A Tutorial on Applications, Opportunities, and Limitations

Dobler, D., Binder, H., Boulesteix, A., Igelmann, J., Köhler, D., Mansmann, U., Pauly, M., Scherag, A., Schmid, M., Al Tawil, A., et al. (2025) · Statistics in Medicine · doi:10.1002/sim.70263 · Cited by 20

Interplay between genome-wide implicated genetic variants and environmental factors related to childhood antisocial behavior in the UK ALSPAC cohort

Ruisch, I. H., Dietrich, A., Glennon, J. C., Buitelaar, J. K., & Hoekstra, P. J. (2019) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-018-0964-5 · Cited by 19

Distinct changes in the life-history strategies of Folsomia candida Willem (Collembola: Isotomidae) due to multi- and transgenerational treatments with an insecticide

Szabó, B., Seres, A., & Bakonyi, G. (2020) · Applied Soil Ecology · doi:10.1016/j.apsoil.2020.103563 · Cited by 19

Vegetation responses to late Holocene climate changes in an Andean forest

Schiferl, J. D., Bush, M. B., Silman, M. R., & Urrego, D. H. (2018) · Quaternary Research · doi:10.1017/qua.2017.64 · Cited by 19

Making it easier for older people to talk to smart homes: the effect of early help prompts

Wolters, K. M., Engelbrecht, K.-P., Gödde, F., Möller, S., Naumann, A., & Schleicher, R. (2010) · Universal Access in the Information Society · doi:10.1007/s10209-009-0184-x · Cited by 18

Finding Associations in Dense Genetic Maps: A Genetic Algorithm Approach

Clark, T. G., De Iorio, M., Griffiths, R. C., & Farrall, M. (2005) · Human Heredity · doi:10.1159/000088845 · Cited by 18

Does Antibiotic Resistance Evolve in Hospitals?

Seigal, A., Mira, P., Sturmfels, B., & Barlow, M. (2017) · Bulletin of Mathematical Biology · doi:10.1007/s11538-016-0232-7 · Cited by 18

Grief, Mindfulness and Neural Predictors of Improvement in Family Dementia Caregivers

Jain, F. A., Connolly, C. G., Moore, L. C., Leuchter, A. F., Abrams, M., Ben-Yelles, R. W., Chang, S. E., Ramirez Gomez, L. A., Huey, N., Lavretsky, H., et al. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2019.00155 · Cited by 18

Race and Socioeconomic Status as Predictors of Willingness to Use Digital Mental Health Interventions or One-On-One Psychotherapy: National Survey Study

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