Generalized Linear Models

The interpretation of interaction in contingency tables

Simpson, E. H. (1951) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1951.tb00088.x · Cited by 2,301

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106

Untitled work

(2001) · RePEc: Research Papers in Economics · Cited by 27,577

Longitudinal data analysis using generalized linear models

LIANG, K.-Y., & ZEGER, S. L. (1986) · Biometrika · doi:10.1093/biomet/73.1.13 · Cited by 18,550

Differential expression analysis for sequence count data

Anders, S., & Huber, W. (2010) · Genome Biology · doi:10.1186/gb-2010-11-10-r106 · Cited by 15,581

Bayesian Measures of Model Complexity and Fit

Spiegelhalter, D. J., Best, N. G., Carlin, B. P., & Van Der Linde, A. (2002) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00353 · Cited by 151

Missing data: our view of the state of the art

Schafer, J. L., & Graham, J. W. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.2.147 · Cited by 11,638

Generalized linear mixed models: a practical guide for ecology and evolution

Bolker, B. M., Brooks, M. E., Clark, C. J., Geange, S. W., Poulsen, J. R., Stevens, M. H. H., & White, J.-S. S. (2009) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2008.10.008 · Cited by 8,910

The adaptive lasso and its oracle properties

Zou, H. (2006) · Journal of the American Statistical Association · doi:10.1198/016214506000000735 · Cited by 7,470

Predictive habitat distribution models in ecology

Guisan, A., & Zimmermann, N. E. (2000) · Ecological Modelling · doi:10.1016/s0304-3800(00)00354-9 · Cited by 7,359

Bayesian model selection in social research

Raftery, A. E. (1995) · Sociological Methodology · doi:10.2307/271063 · Cited by 6,823

voom: precision weights unlock linear model analysis tools for RNA-seq read counts

Law, C. W., Chen, Y., Shi, W., & Smyth, G. K. (2014) · Genome Biology · doi:10.1186/gb-2014-15-2-r29 · Cited by 6,155

A working guide to boosted regression trees

Elith, J., Leathwick, J. R., & Hastie, T. (2008) · Journal of Animal Ecology · doi:10.1111/j.1365-2656.2008.01390.x · Cited by 6,484

Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation

McCarthy, D. J., Chen, Y., & Smyth, G. K. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks042 · Cited by 5,195

AIC model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons

Burnham, K. P., Anderson, D. R., & Huyvaert, K. P. (2011) · Behavioral Ecology and Sociobiology · doi:10.1007/s00265-010-1029-6 · Cited by 4,104

Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing

Lambert, D. (1992) · Technometrics · doi:10.2307/1269547 · Cited by 3,988

Case Selection Techniques in Case Study Research: A Menu of Qualitative and Quantitative Options

Seawright, J., & Gerring, J. (2008) · Political Research Quarterly · doi:10.1177/1065912907313077 · Cited by 3,827

Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study

Pearce, M. S., Salotti, J. A., Little, M. P., McHugh, K., Lee, C., Kim, K. P., Howe, N. L., Ronckers, C. M., Rajaraman, P., Craft, A. W., et al. (2012) · The Lancet · doi:10.1016/s0140-6736(12)60815-0 · Cited by 3,735

Methods to account for spatial autocorrelation in the analysis of species distributional data: a review.

F. Dormann, C., M. McPherson, J., B. Araújo, M., Bivand, R., Bolliger, J., Carl, G., G. Davies, R., Hirzel, A., Jetz, W., Daniel Kissling, W., et al. (2007) · Ecography · doi:10.1111/j.2007.0906-7590.05171.x · Cited by 3,433

SOMETHING OLD, SOMETHING NEW: A LONGITUDINAL STUDY OF SEARCH BEHAVIOR AND NEW PRODUCT INTRODUCTION.

Katila, R., & Ahuja, G. (2002) · Academy of Management Journal · doi:10.2307/3069433 · Cited by 3,640

Econometric Models for Count Data with an Application to the Patents-R & D Relationship

Hausman, J., Hall, B. H., & Griliches, Z. (1984) · Econometrica · doi:10.2307/1911191 · Cited by 3,393

Categorical data analysis: Away from ANOVAs (transformation or not) and towards logit mixed models

Jaeger, T. F. (2008) · Journal of Memory and Language · doi:10.1016/j.jml.2007.11.007 · Cited by 3,317

What is subjective global assessment of nutritional status?

Detsky, A., McLaughlin, Baker, J., Johnston, N., Whittaker, S., Mendelson, R., & Jeejeebhoy, K. (1987) · Journal of Parenteral and Enteral Nutrition · doi:10.1177/014860718701100108 · Cited by 3,252

Multiple imputation of discrete and continuous data by fully conditional specification

van Buuren, S. (2007) · Statistical Methods in Medical Research · doi:10.1177/0962280206074463 · Cited by 2,827

RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays

Marioni, J. C., Mason, C. E., Mane, S. M., Stephens, M., & Gilad, Y. (2008) · Genome Research · doi:10.1101/gr.079558.108 · Cited by 2,771

Beta Regression in R

Cribari-Neto, F., & Zeileis, A. (2010) · Journal of Statistical Software · doi:10.18637/jss.v034.i02 · Cited by 2,505

Simulation Study of Confounder-Selection Strategies

Maldonado, G., & Greenland, S. (1993) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a116813 · Cited by 2,491

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

A modified test for small‐study effects in meta‐analyses of controlled trials with binary endpoints

Harbord, R. M., Egger, M., & Sterne, J. A. C. (2006) · Statistics in Medicine · doi:10.1002/sim.2380 · Cited by 2,267

Prevalence and Burden of Migraine in the United States: Data From the American Migraine Study II

Lipton, R. B., Stewart, W. F., Diamond, S., Diamond, M. L., & Reed, M. (2001) · Headache: The Journal of Head and Face Pain · doi:10.1046/j.1526-4610.2001.041007646.x · Cited by 2,268

Modeling and variable selection in epidemiologic analysis

Greenland, S. (1989) · American Journal of Public Health · doi:10.2105/ajph.79.3.340 · Cited by 2,208

Normalization of RNA-seq data using factor analysis of control genes or samples

Risso, D., Ngai, J., Speed, T. P., & Dudoit, S. (2014) · Nature Biotechnology · doi:10.1038/nbt.2931 · Cited by 2,052

A simple regression method for mapping quantitative trait loci in line crosses using flanking markers

Haley, C. S., & Knott, S. A. (1992) · Heredity · doi:10.1038/hdy.1992.131 · Cited by 1,991

Using Bayesian model averaging to calibrate forecast ensembles.

Raftery, A. E., Gneiting, T., Balabdaoui, F., & Polakowski, M. (2005) · Monthly Weather Review · doi:10.1175/mwr2906.1 · Cited by 1,915

Default Bayes factors for ANOVA designs

Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2012.08.001 · Cited by 1,800

A better lemon squeezer? maximum-likelihood regression with beta-distributed dependent variables.

Smithson, M., & Verkuilen, J. (2006) · Psychological Methods · doi:10.1037/1082-989x.11.1.54 · Cited by 1,788

Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments

Bullard, J. H., Purdom, E., Hansen, K. D., & Dudoit, S. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-94 · Cited by 1,680

What you see may not be what you get: a brief, nontechnical introduction to overfitting in regression-type models

Babyak, M. A. (2004) · Psychosomatic Medicine · doi:10.1097/01.psy.0000127692.23278.a9 · Cited by 2,061

Estimating log models: to transform or not to transform?

Manning, W. G., & Mullahy, J. (2001) · Journal of Health Economics · doi:10.1016/s0167-6296(01)00086-8 · Cited by 1,790

Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids

Häubl, G., & Trifts, V. (2000) · Marketing Science · doi:10.1287/mksc.19.1.4.15178 · Cited by 1,731

Detecting differential usage of exons from RNA-seq data

Anders, S., Reyes, A., & Huber, W. (2012) · Genome Research · doi:10.1101/gr.133744.111 · Cited by 1,545

Effect of intensive diabetes treatment on the development and progression of long-term complications in adolescents with insulin-dependent diabetes mellitus: Diabetes Control and Complications Trial

(1994) · The Journal of Pediatrics · doi:10.1016/s0022-3476(94)70190-3 · Cited by 1,654

WHAT IS THE OBSERVED RELATIONSHIP BETWEEN SPECIES RICHNESS AND PRODUCTIVITY?

Mittelbach, G. G., Steiner, C. F., Scheiner, S. M., Gross, K. L., Reynolds, H. L., Waide, R. B., Willig, M. R., Dodson, S. I., & Gough, L. (2001) · Ecology · doi:10.1890/0012-9658(2001)082[2381:witorb]2.0.co;2 · Cited by 1,650

The theoretical status of latent variables.

Borsboom, D., Mellenbergh, G. J., & van Heerden, J. (2003) · Psychological Review · doi:10.1037/0033-295x.110.2.203 · Cited by 1,566

Complex Sample Data in Structural Equation Modeling

Muthen, B. O., & Satorra, A. (1995) · Sociological Methodology · doi:10.2307/271070 · Cited by 1,586

Feature selection, L 1 vs. L 2 regularization, and rotational invariance

Ng, A. Y. (2004) · Twenty-first international conference on Machine learning - ICML '04 · doi:10.1145/1015330.1015435 · Cited by 1,572

Biodiversity and ecosystem multifunctionality

Hector, A., & Bagchi, R. (2007) · Nature · doi:10.1038/nature05947 · Cited by 1,412

Group representations in probability and statistics

Diaconis, P. (1988) · doi:10.1214/lnms/1215467407 · Cited by 1,381

Detecting gene–gene interactions that underlie human diseases

Cordell, H. J. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2579 · Cited by 1,350

Standardizing catch and effort data: a review of recent approaches

Maunder, M. N., & Punt, A. E. (2004) · Fisheries Research · doi:10.1016/j.fishres.2004.08.002 · Cited by 1,336

Improving imbalanced learning through a heuristic oversampling method based on k-means and SMOTE

Douzas, G., Bacao, F., & Last, F. (2018) · Information Sciences · doi:10.1016/j.ins.2018.06.056 · Cited by 1,277

Quasi-Poisson vs. negative binomial regression: how should we model overdispersed count data?

Ver Hoef, J. M., & Boveng, P. L. (2007) · Ecology · doi:10.1890/07-0043.1 · Cited by 1,238

Ozone and short-term mortality in 95 US urban communities, 1987–2000

Bell, M. L. (2004) · JAMA · doi:10.1001/jama.292.19.2372 · Cited by 1,202

Dimensionality reduction for large-scale neural recordings

Cunningham, J. P., & Yu, B. M. (2014) · Nature Neuroscience · doi:10.1038/nn.3776 · Cited by 1,219

Hippocampal ‘time cells’ bridge the gap in memory for discontiguous events

MacDonald, C. J., Lepage, K. Q., Eden, U. T., & Eichenbaum, H. (2011) · Neuron · doi:10.1016/j.neuron.2011.07.012 · Cited by 1,193

Continuous Positive Airway Pressure for Central Sleep Apnea and Heart Failure

Bradley, T. D., Logan, A. G., Kimoff, R. J., Sériès, F., Morrison, D., Ferguson, K., Belenkie, I., Pfeifer, M., Fleetham, J., Hanly, P., et al. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa051001 · Cited by 1,189

The analysis of count data: a gentle introduction to poisson regression and its alternatives.

Coxe, S., West, S. G., & Aiken, L. S. (2009) · Journal of Personality Assessment · doi:10.1080/00223890802634175 · Cited by 1,172

Transitions between frailty states among community-living older persons

Gill, T. M., Gahbauer, E. A., Allore, H. G., & Han, L. (2006) · Archives of Internal Medicine · doi:10.1001/archinte.166.4.418 · Cited by 1,141

Foundations of Machine Learning

Mohri, M., Rostamizadeh, A., & Talwalkar, A. (2018) · doi:10.7551/mitpress/10290.001.0001 · Cited by 1,122

Some aspects of the spline smoothing approach to non-parametric regression curve fitting

Silverman, B. W. (1985) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1985.tb01327.x · Cited by 1,117

Mapping Species Distributions with MAXENT Using a Geographically Biased Sample of Presence Data: A Performance Assessment of Methods for Correcting Sampling Bias

Fourcade, Y., Engler, J. O., Rödder, D., & Secondi, J. (2014) · PLoS ONE · doi:10.1371/journal.pone.0097122 · Cited by 1,098

First person experience of body transfer in virtual reality

Slater, M., Spanlang, B., Sanchez-Vives, M. V., & Blanke, O. (2010) · PLoS ONE · doi:10.1371/journal.pone.0010564 · Cited by 1,090

High resolution of quantitative traits into multiple loci via interval mapping.

Jansen, R. C., & Stam, P. (1994) · Genetics · doi:10.1093/genetics/136.4.1447 · Cited by 1,046

Rare-Variant Association Analysis: Study Designs and Statistical Tests

Lee, S., Abecasis, G. R., Boehnke, M., & Lin, X. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.06.009 · Cited by 1,042

Identification and Review of Sensitivity Analysis Methods

Christopher Frey, H., & Patil, S. R. (2002) · Risk Analysis · doi:10.1111/0272-4332.00039 · Cited by 1,036

Losers and winners in coral reefs acclimatized to elevated carbon dioxide concentrations

Fabricius, K. E., Langdon, C., Uthicke, S., Humphrey, C., Noonan, S., De’ath, G., Okazaki, R., Muehllehner, N., Glas, M. S., & Lough, J. M. (2011) · Nature Climate Change · doi:10.1038/nclimate1122 · Cited by 1,006

Logistic regression, survival analysis, and the Kaplan-Meier curve.

Efron, B. (1988) · Journal of the American Statistical Association · doi:10.1080/01621459.1988.10478612 · Cited by 1,065

On the Variances of Asymptotically Normal Estimators from Complex Surveys

Binder, D. A. (1983) · International Statistical Review / Revue Internationale de Statistique · doi:10.2307/1402588 · Cited by 982

How big is big enough?”: sample size and goodness of fit in structural equation models with latent variables

Tanaka, J. S. (1987) · Child Development · doi:10.2307/1130296 · Cited by 982

Developing indicators for European birds

Gregory, R. D., van Strien, A., Vorisek, P., Gmelig Meyling, A. W., Noble, D. G., Foppen, R. P. B., & Gibbons, D. W. (2005) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2004.1602 · Cited by 948

Regression and model-building in conservation biology, biogeography and ecology: The distinction between – and reconciliation of – ‘predictive’ and ‘explanatory’ models

Mac Nally, R. (2000) · Biodiversity & Conservation · doi:10.1023/a:1008985925162 · Cited by 938

Functional relevance of cross-modal plasticity in blind humans

Cohen, L. G., Celnik, P., Pascual-Leone, A., Corwell, B., Faiz, L., Dambrosia, J., Honda, M., Sadato, N., Gerloff, C., Catala´, M. D., et al. (1997) · Nature · doi:10.1038/38278 · Cited by 911

Dose, volume, and function relationships in parotid salivary glands following conformal and intensity-modulated irradiation of head and neck cancer

Eisbruch, A., Ten Haken, R. K., Kim, H. M., Marsh, L. H., & Ship, J. A. (1999) · International Journal of Radiation Oncology*Biology*Physics · doi:10.1016/s0360-3016(99)00247-3 · Cited by 922

A program to prevent functional decline in physically frail, elderly persons who live at home

Gill, T. M., Baker, D. I., Gottschalk, M., Peduzzi, P. N., Allore, H., & Byers, A. (2002) · New England Journal of Medicine · doi:10.1056/nejmoa020423 · Cited by 871

On the relationship between farmland biodiversity and land-use intensity in Europe

Kleijn, D., Kohler, F., Báldi, A., Batáry, P., Concepción, E. D., Clough, Y., Díaz, M., Gabriel, D., Holzschuh, A., Knop, E., et al. (2009) · Proceedings of the Royal Society B: Biological Sciences · doi:10.1098/rspb.2008.1509 · Cited by 868

An Analysis of the New York City Police Department's “Stop-and-Frisk” Policy in the Context of Claims of Racial Bias

Gelman, A., Fagan, J., & Kiss, A. (2007) · Journal of the American Statistical Association · doi:10.1198/016214506000001040 · Cited by 873

Anatomy of hierarchy: Feedforward and feedback pathways in macaque visual cortex

Markov, N. T., Vezoli, J., Chameau, P., Falchier, A., Quilodran, R., Huissoud, C., Lamy, C., Misery, P., Giroud, P., Ullman, S., et al. (2014) · Journal of Comparative Neurology · doi:10.1002/cne.23458 · Cited by 759

Gut Microbiome Metagenomics Analysis Suggests a Functional Model for the Development of Autoimmunity for Type 1 Diabetes

Brown, C. T., Davis-Richardson, A. G., Giongo, A., Gano, K. A., Crabb, D. B., Mukherjee, N., Casella, G., Drew, J. C., Ilonen, J., Knip, M., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0025792 · Cited by 778

Statistical tests of models of DNA substitution

Goldman, N. (1993) · Journal of Molecular Evolution · doi:10.1007/bf00166252 · Cited by 736

Reconsidering peers and delinquency: How do peers matter?

Haynie, D. L., & Osgood, D. W. (2005) · Social Forces · doi:10.1353/sof.2006.0018 · Cited by 756

Linking agricultural practice to insect and bird populations: a historical study over three decades

Benton, T. G., Bryant, D. M., Cole, L., & Crick, H. Q. P. (2002) · Journal of Applied Ecology · doi:10.1046/j.1365-2664.2002.00745.x · Cited by 718

Risk of stroke early after transient ischaemic attack: a systematic review and meta-analysis

Giles, M. F., & Rothwell, P. M. (2007) · The Lancet Neurology · doi:10.1016/s1474-4422(07)70274-0 · Cited by 676

Trends in the prevalence of preexisting diabetes and gestational diabetes mellitus among a racially/ethnically diverse population of pregnant women, 1999–2005

Lawrence, J. M., Contreras, R., Chen, W., & Sacks, D. A. (2008) · Diabetes Care · doi:10.2337/dc07-2345 · Cited by 658

The uncertain nature of absences and their importance in species distribution modelling

Lobo, J. M., Jiménez‐Valverde, A., & Hortal, J. (2010) · Ecography · doi:10.1111/j.1600-0587.2009.06039.x · Cited by 656

Migraine in the United States: Epidemiology and patterns of health care use

Lipton, R. B., Scher, A. I., Kolodner, K., Liberman, J., Steiner, T. J., & Stewart, W. F. (2002) · Neurology · doi:10.1212/wnl.58.6.885 · Cited by 616

Physical distancing interventions and incidence of coronavirus disease 2019: natural experiment in 149 countries

Islam, N., Sharp, S. J., Chowell, G., Shabnam, S., Kawachi, I., Lacey, B., Massaro, J. M., D’Agostino, R. B., & White, M. (2020) · BMJ · doi:10.1136/bmj.m2743 · Cited by 601

Social-psychological factors affecting help-seeking for emotional problems

Rickwood, D. J., & Braithwaite, V. A. (1994) · Social Science & Medicine · doi:10.1016/0277-9536(94)90099-x · Cited by 583

Agricultural runoff fuels large phytoplankton blooms in vulnerable areas of the ocean

Michael Beman, J., Arrigo, K. R., & Matson, P. A. (2005) · Nature · doi:10.1038/nature03370 · Cited by 581

Social Anxiety Disorder and the Risk of Depression: A Prospective Community Study of Adolescents and Young Adults

Stein, M. B., Fuetsch, M., Müller, N., Höfler, M., Lieb, R., & Wittchen, H.-U. (2001) · Archives of General Psychiatry · doi:10.1001/archpsyc.58.3.251 · Cited by 573

Regression and ordered categorical variables

Anderson, J. A. (1984) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1984.tb01270.x · Cited by 574

Towards a digital body: the virtual arm illusion

Slater, M. (2008) · Frontiers in Human Neuroscience · doi:10.3389/neuro.09.006.2008 · Cited by 570

RECOGNITION AND SELECTION OF SETTLEMENT SUBSTRATA DETERMINE POST-SETTLEMENT SURVIVAL IN CORALS

Harrington, L., Fabricius, K., De'ath, G., & Negri, A. (2004) · Ecology · doi:10.1890/04-0298 · Cited by 568

Doing Bayesian Data Analysis: A Tutorial with R and BUGS

Barry, J. (2011) · Europe’s Journal of Psychology · doi:10.5964/ejop.v7i4.163 · Cited by 563

Beyond t test and ANOVA: applications of mixed-effects models for more rigorous statistical analysis in neuroscience research

Yu, Z., Guindani, M., Grieco, S. F., Chen, L., Holmes, T. C., & Xu, X. (2022) · Neuron · doi:10.1016/j.neuron.2021.10.030 · Cited by 563

Common genetic variants of the FADS1 FADS2 gene cluster and their reconstructed haplotypes are associated with the fatty acid composition in phospholipids

Schaeffer, L., Gohlke, H., Müller, M., Heid, I. M., Palmer, L. J., Kompauer, I., Demmelmair, H., Illig, T., Koletzko, B., & Heinrich, J. (2006) · Human Molecular Genetics · doi:10.1093/hmg/ddl117 · Cited by 561

Age-associated decrease in TLR function in primary human dendritic cells predicts influenza vaccine response

Panda, A., Qian, F., Mohanty, S., van Duin, D., Newman, F. K., Zhang, L., Chen, S., Towle, V., Belshe, R. B., Fikrig, E., et al. (2010) · The Journal of Immunology · doi:10.4049/jimmunol.0901022 · Cited by 548

Persistent psychopathology and neurocognitive impairment in COVID-19 survivors: effect of inflammatory biomarkers at three-month follow-up

Mazza, M. G., Palladini, M., De Lorenzo, R., Magnaghi, C., Poletti, S., Furlan, R., Ciceri, F., Rovere-Querini, P., & Benedetti, F. (2021) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2021.02.021 · Cited by 513

Insomnia and the Performance of US Workers: Results from the America Insomnia Survey

Kessler, R. C., Berglund, P. A., Coulouvrat, C., Hajak, G., Roth, T., Shahly, V., Shillington, A. C., Stephenson, J. J., & Walsh, J. K. (2011) · Sleep · doi:10.5665/sleep.1230 · Cited by 527

Improving Quality Improvement Using Achievable Benchmarks For Physician Feedback: A Randomized Controlled Trial

Kiefe, C. I., Allison, J. J., Williams, O. D., Person, S. D., Weaver, M. T., & Weissman, N. W. (2001) · JAMA · doi:10.1001/jama.285.22.2871 · Cited by 503

The Exposure–Response Curve for Ozone and Risk of Mortality and the Adequacy of Current Ozone Regulations

Bell, M. L., Peng, R. D., & Dominici, F. (2006) · Environmental Health Perspectives · doi:10.1289/ehp.8816 · Cited by 481

Thelarche, pubarche, and menarche attainment in children with normal and elevated body mass index

Rosenfield, R. L., Lipton, R. B., & Drum, M. L. (2009) · PEDIATRICS · doi:10.1542/peds.2008-0146 · Cited by 499