WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility

Equation of State Calculations by Fast Computing Machines

Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953) · The Journal of Chemical Physics · doi:10.1063/1.1699114 · Cited by 37,192

Bayesian Data Analysis

Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2003) · doi:10.1201/9780429258480 · Cited by 27,276

Sampling-based approaches to calculating marginal densities

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Random effects structure for confirmatory hypothesis testing: Keep it maximal

Barr, D. J., Levy, R., Scheepers, C., & Tily, H. J. (2013) · Journal of Memory and Language · doi:10.1016/j.jml.2012.11.001 · Cited by 10,328

brms : An R Package for Bayesian Multilevel Models Using Stan

Bürkner, P.-C. (2017) · Journal of Statistical Software · doi:10.18637/jss.v080.i01 · Cited by 9,476

Stan : A Probabilistic Programming Language

Carpenter, B., Gelman, A., Hoffman, M. D., Lee, D., Goodrich, B., Betancourt, M., Brubaker, M., Guo, J., Li, P., & Riddell, A. (2017) · Journal of Statistical Software · doi:10.18637/jss.v076.i01 · Cited by 7,754

Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial

Salanti, G., Ades, A. E., & Ioannidis, J. P. A. (2011) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2010.03.016 · Cited by 3,766

Probabilistic machine learning and artificial intelligence

Ghahramani, Z. (2015) · Nature · doi:10.1038/nature14541 · Cited by 1,995

Analysing data and undertaking meta‐analyses

Deeks, J. J., Higgins, J. P., Altman, D. G., & on behalf of the Cochrane Statistical Methods Group (2019) · Cochrane Handbook for Systematic Reviews of Interventions · doi:10.1002/9781119536604.ch10 · Cited by 2,672

The BUGS project: evolution, critique and future directions

Lunn, D., Spiegelhalter, D., Thomas, A., & Best, N. (2009) · Statistics in Medicine · doi:10.1002/sim.3680 · Cited by 1,876

Rank-Normalization, Folding, and Localization: An Improved Rˆ for Assessing Convergence of MCMC (with Discussion)

Vehtari, A., Gelman, A., Simpson, D., Carpenter, B., & Bürkner, P.-C. (2021) · Bayesian Analysis · doi:10.1214/20-ba1221 · Cited by 1,810

Analysing Data and Undertaking Meta‐Analyses

Deeks, J. J., Higgins, J. P., & Altman, D. G. (2008) · Cochrane Handbook for Systematic Reviews of Interventions · doi:10.1002/9780470712184.ch9 · Cited by 1,800

Indirect and mixed‐treatment comparison, network, or multiple‐treatments meta‐analysis: many names, many benefits, many concerns for the next generation evidence synthesis tool

Salanti, G. (2012) · Research Synthesis Methods · doi:10.1002/jrsm.1037 · Cited by 1,729

Methods to estimate the between‐study variance and its uncertainty in meta‐analysis

Veroniki, A. A., Jackson, D., Viechtbauer, W., Bender, R., Bowden, J., Knapp, G., Kuss, O., Higgins, J. P., Langan, D., & Salanti, G. (2016) · Research Synthesis Methods · doi:10.1002/jrsm.1164 · Cited by 1,685

The long-term effect of lifestyle interventions to prevent diabetes in the China Da Qing Diabetes Prevention Study: a 20-year follow-up study

Li, G., Zhang, P., Wang, J., Gregg, E. W., Yang, W., Gong, Q., Li, H., Li, H., Jiang, Y., An, Y., et al. (2008) · The Lancet · doi:10.1016/s0140-6736(08)60766-7 · Cited by 1,600

Untitled work

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Evidence Synthesis for Decision Making 2: A Generalized Linear Modeling Framework for Pairwise and Network Meta-analysis of Randomized Controlled Trials

Dias, S., Sutton, A. J., Ades, A. E., & Welton, N. J. (2013) · Medical Decision Making · doi:10.1177/0272989x12458724 · Cited by 1,207

Consistency and inconsistency in network meta-analysis: model estimation using multivariate meta-regression

White, I. R., Barrett, J. K., Jackson, D., & Higgins, J. P. T. (2012) · Research Synthesis Methods · doi:10.1002/jrsm.1045 · Cited by 1,114

Methodological issues and advances in biological meta-analysis

Nakagawa, S., & Santos, E. S. A. (2012) · Evolutionary Ecology · doi:10.1007/s10682-012-9555-5 · Cited by 1,032

topicmodels : An R Package for Fitting Topic Models

Grün, B., & Hornik, K. (2011) · Journal of Statistical Software · doi:10.18637/jss.v040.i13 · Cited by 1,072

Influence of Reported Study Design Characteristics on Intervention Effect Estimates From Randomized, Controlled Trials

Savović, J., Jones, H. E., Altman, D. G., Harris, R. J., Jüni, P., Pildal, J., Als-Nielsen, B., Balk, E. M., Gluud, C., Gluud, L. L., et al. (2012) · Annals of Internal Medicine · doi:10.7326/0003-4819-157-6-201209180-00537 · Cited by 1,049

Metan: fixed- and random-effects meta-analysis

Harris, R. J., Deeks, J. J., Altman, D. G., Bradburn, M. J., Harbord, R. M., & Sterne, J. A. C. (2008) · The Stata Journal: Promoting communications on statistics and Stata · doi:10.1177/1536867x0800800102 · Cited by 1,027

Statistical Evidence in Experimental Psychology: An Empirical Comparison Using 855 t Tests

Wetzels, R., Matzke, D., Lee, M. D., Rouder, J. N., Iverson, G. J., & Wagenmakers, E.-J. (2011) · Perspectives on Psychological Science · doi:10.1177/1745691611406923 · Cited by 945

Stability of pollination services decreases with isolation from natural areas despite honey bee visits: Habitat isolation and pollination stability

Garibaldi, L. A., Steffan-Dewenter, I., Kremen, C., Morales, J. M., Bommarco, R., Cunningham, S. A., Carvalheiro, L. G., Chacoff, N. P., Dudenhöffer, J. H., Greenleaf, S. S., et al. (2011) · Ecology Letters · doi:10.1111/j.1461-0248.2011.01669.x · Cited by 962

Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews

Turner, R. M., Davey, J., Clarke, M. J., Thompson, S. G., & Higgins, J. P. (2012) · International Journal of Epidemiology · doi:10.1093/ije/dys041 · Cited by 837

Bayesian hypothesis testing for psychologists: A tutorial on the Savage–Dickey method

Wagenmakers, E.-J., Lodewyckx, T., Kuriyal, H., & Grasman, R. (2010) · Cognitive Psychology · doi:10.1016/j.cogpsych.2009.12.001 · Cited by 740

Psychological and pharmacological interventions for social anxiety disorder in adults: a systematic review and network meta-analysis

Mayo-Wilson, E., Dias, S., Mavranezouli, I., Kew, K., Clark, D. M., Ades, A. E., & Pilling, S. (2014) · The Lancet Psychiatry · doi:10.1016/s2215-0366(14)70329-3 · Cited by 680

Democracy as a Latent Variable

Treier, S., & Jackman, S. (2008) · American Journal of Political Science · doi:10.1111/j.1540-5907.2007.00308.x · Cited by 680

Influence of reported study design characteristics on intervention effect estimates from randomised controlled trials: combined analysis of meta-epidemiological studies

Savović, J., Jones, H., Altman, D., Harris, R., Jűni, P., Pildal, J., Als-Nielsen, B., Balk, E., Gluud, C., Gluud, L., et al. (2012) · Health Technology Assessment · doi:10.3310/hta16350 · Cited by 668

Variational Message Passing

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The global burden of listeriosis: a systematic review and meta-analysis

de Noordhout, C. M., Devleesschauwer, B., Angulo, F. J., Verbeke, G., Haagsma, J., Kirk, M., Havelaar, A., & Speybroeck, N. (2014) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(14)70870-9 · Cited by 624

Church: a language for generative models

Goodman, N., Mansinghka, V., Roy, D. M., Bonawitz, K., & Tenenbaum, J. B. (2012) · arXiv · doi:10.48550/arxiv.1206.3255 · Cited by 577

Multivariate meta‐analysis: Potential and promise

Jackson, D., Riley, R., & White, I. R. (2011) · Statistics in Medicine · doi:10.1002/sim.4172 · Cited by 530

Systematic review: Hygiene and health: systematic review of handwashing practices worldwide and update of health effects

Freeman, M. C., Stocks, M. E., Cumming, O., Jeandron, A., Higgins, J. P. T., Wolf, J., Prüss‐Ustün, A., Bonjour, S., Hunter, P. R., Fewtrell, L., et al. (2014) · Tropical Medicine & International Health · doi:10.1111/tmi.12339 · Cited by 524

Using network meta‐analysis to evaluate the existence of small‐study effects in a network of interventions

Chaimani, A., & Salanti, G. (2012) · Research Synthesis Methods · doi:10.1002/jrsm.57 · Cited by 521

Population Pharmacokinetics of Therapeutic Monoclonal Antibodies

Dirks, N. L., & Meibohm, B. (2010) · Clinical Pharmacokinetics · doi:10.2165/11535960-000000000-00000 · Cited by 500

The natural history of Chlamydia trachomatis infection in women: a multi-parameter evidence synthesis

Price, M. J., Ades, A., Soldan, K., Welton, N. J., Macleod, J., Simms, I., DeAngelis, D., Turner, K. M., & Horner, P. J. (2016) · Health Technology Assessment · doi:10.3310/hta20220 · Cited by 494

Effects of weight loss interventions for adults who are obese on mortality, cardiovascular disease, and cancer: systematic review and meta-analysis

Ma, C., Avenell, A., Bolland, M., Hudson, J., Stewart, F., Robertson, C., Sharma, P., Fraser, C., & MacLennan, G. (2017) · BMJ · doi:10.1136/bmj.j4849 · Cited by 464

Systematic review: Assessing the impact of drinking water and sanitation on diarrhoeal disease in low‐ and middle‐income settings: systematic review and meta‐regression

Wolf, J., Prüss‐Ustün, A., Cumming, O., Bartram, J., Bonjour, S., Cairncross, S., Clasen, T., Colford, J. M., Curtis, V., De France, J., et al. (2014) · Tropical Medicine & International Health · doi:10.1111/tmi.12331 · Cited by 461

Improving transparency and replication in Bayesian statistics: The WAMBS-Checklist.

Depaoli, S., & van de Schoot, R. (2017) · Psychological Methods · doi:10.1037/met0000065 · Cited by 448

A two decade dementia incidence comparison from the Cognitive Function and Ageing Studies I and II

Matthews, F. E., Stephan, B. C. M., Robinson, L., Jagger, C., Barnes, L. E., Arthur, A., Brayne, C., Cognitive Function and Ageing Studies (CFAS) Collaboration, Comas-Herrera, A., Wittenberg, R., et al. (2016) · Nature Communications · doi:10.1038/ncomms11398 · Cited by 426

Predictive distributions for between‐study heterogeneity and simple methods for their application in Bayesian meta‐analysis

Turner, R. M., Jackson, D., Wei, Y., Thompson, S. G., & Higgins, J. P. T. (2015) · Statistics in Medicine · doi:10.1002/sim.6381 · Cited by 410

Impact of drinking water, sanitation and handwashing with soap on childhood diarrhoeal disease: updated meta-analysis and meta-regression

Wolf, J., Hunter, P. R., Freeman, M. C., Cumming, O., Clasen, T., Bartram, J., Higgins, J. P. T., Johnston, R., Medlicott, K., Boisson, S., et al. (2018) · Tropical Medicine & International Health · doi:10.1111/tmi.13051 · Cited by 403

GetReal in network meta-analysis: a review of the methodology

Efthimiou, O., Debray, T. P. A., van Valkenhoef, G., Trelle, S., Panayidou, K., Moons, K. G. M., Reitsma, J. B., Shang, A., Salanti, G., & on behalf of GetReal Methods Review Group (2016) · Research Synthesis Methods · doi:10.1002/jrsm.1195 · Cited by 401

Pharmacological treatments for generalised anxiety disorder: A systematic review and network meta-analysis

Slee, A., Nazareth, I., Bondaronek, P., Liu, Y., Cheng, Z., & Freemantle, N. (2019) · The Lancet · doi:10.1016/s0140-6736(18)31793-8 · Cited by 372

Meta-Analysis of the Relationship Between Non–High-Density Lipoprotein Cholesterol Reduction and Coronary Heart Disease Risk

Robinson, J. G., Wang, S., Smith, B. J., & Jacobson, T. A. (2009) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2008.10.024 · Cited by 368

blavaan : Bayesian Structural Equation Models via Parameter Expansion

Merkle, E. C., & Rosseel, Y. (2018) · Journal of Statistical Software · doi:10.18637/jss.v085.i04 · Cited by 360

Minimal clinically important difference on the Beck Depression Inventory—II according to the patient's perspective.

Button, K. S., Kounali, D., Thomas, L., Wiles, N. J., Peters, T. J., Welton, N. J., Ades, A. E., & Lewis, G. (2015) · Psychological Medicine · doi:10.1017/s0033291715001270 · Cited by 332

How does exercise treatment compare with antihypertensive medications? A network meta-analysis of 391 randomised controlled trials assessing exercise and medication effects on systolic blood pressure

Naci, H., Salcher-Konrad, M., Dias, S., Blum, M. R., Sahoo, S. A., Nunan, D., & Ioannidis, J. P. A. (2019) · British Journal of Sports Medicine · doi:10.1136/bjsports-2018-099921 · Cited by 326

Much of late life cognitive decline is not due to common neurodegenerative pathologies

Boyle, P. A., Wilson, R. S., Yu, L., Barr, A. M., Honer, W. G., Schneider, J. A., & Bennett, D. A. (2013) · Annals of Neurology · doi:10.1002/ana.23964 · Cited by 323

Computerized cognitive training and functional recovery in major depressive disorder: A meta-analysis

Motter, J. N., Pimontel, M. A., Rindskopf, D., Devanand, D. P., Doraiswamy, P. M., & Sneed, J. R. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2015.09.022 · Cited by 303

Comparing the Similarity of Responses Received from Studies in Amazon’s Mechanical Turk to Studies Conducted Online and with Direct Recruitment

Bartneck, C., Duenser, A., Moltchanova, E., & Zawieska, K. (2015) · PLOS ONE · doi:10.1371/journal.pone.0121595 · Cited by 317

Small studies are more heterogeneous than large ones: a meta-meta-analysis

IntHout, J., Ioannidis, J. P. A., Borm, G. F., & Goeman, J. J. (2015) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2015.03.017 · Cited by 314

A direct test of the diathesis-stress model for depression

Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Colodro-Conde, L., Couvy-Duchesne, B., Zhu, G., Coventry, W. L., Byrne, E. M., Gordon, S., Wright, M. J., Montgomery, G. W., Madden, P. A. F., et al. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.130 · Cited by 285

The enduring impact of historical and structural racism on urban violence in Philadelphia

Jacoby, S. F., Dong, B., Beard, J. H., Wiebe, D. J., & Morrison, C. N. (2018) · Social Science & Medicine · doi:10.1016/j.socscimed.2017.05.038 · Cited by 289

Exercise training and resting blood pressure: a large-scale pairwise and network meta-analysis of randomised controlled trials

Edwards, J. J., Deenmamode, A. H. P., Griffiths, M., Arnold, O., Cooper, N. J., Wiles, J. D., & O'Driscoll, J. M. (2023) · British Journal of Sports Medicine · doi:10.1136/bjsports-2022-106503 · Cited by 284

A tutorial on bridge sampling

Gronau, Q. F., Sarafoglou, A., Matzke, D., Ly, A., Boehm, U., Marsman, M., Leslie, D. S., Forster, J. J., Wagenmakers, E.-J., & Steingroever, H. (2017) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2017.09.005 · Cited by 284

Impact of different training modalities on glycaemic control and blood lipids in patients with type 2 diabetes: a systematic review and network meta-analysis

Schwingshackl, L., Missbach, B., Dias, S., König, J., & Hoffmann, G. (2014) · Diabetologia · doi:10.1007/s00125-014-3303-z · Cited by 264

A practical introduction to multivariate meta-analysis

Mavridis, D., & Salanti, G. (2013) · Statistical Methods in Medical Research · doi:10.1177/0962280211432219 · Cited by 255

Toward a principled Bayesian workflow in cognitive science.

Schad, D. J., Betancourt, M., & Vasishth, S. (2021) · Psychological Methods · doi:10.1037/met0000275 · Cited by 252

Xpert® MTB/RIF assay for pulmonary tuberculosis and rifampicin resistance in adults

Steingart, K. R., Sohn, H., Schiller, I., Kloda, L. A., Boehme, C. C., Pai, M., & Dendukuri, N. (2013) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd009593.pub2 · Cited by 253

Methods to calculate uncertainty in the estimated overall effect size from a random‐effects meta‐analysis

Veroniki, A. A., Jackson, D., Bender, R., Kuss, O., Langan, D., Higgins, J. P. T., Knapp, G., & Salanti, G. (2019) · Research Synthesis Methods · doi:10.1002/jrsm.1319 · Cited by 236

Elderspeak communication: impact on dementia care

Williams, K. N., Herman, R., Gajewski, B., & Wilson, K. (2009) · American Journal of Alzheimer's Disease & Other Dementias® · doi:10.1177/1533317508318472 · Cited by 251

Psychometric analysis of the Generalized Anxiety Disorder scale (GAD-7) in primary care using modern item response theory

Jordan, P., Shedden-Mora, M. C., & Löwe, B. (2017) · PLOS ONE · doi:10.1371/journal.pone.0182162 · Cited by 225

Xpert ® MTB/RIF assay for extrapulmonary tuberculosis and rifampicin resistance

Kohli, M., Schiller, I., Dendukuri, N., Dheda, K., Denkinger, C. M., Schumacher, S. G., & Steingart, K. R. (2018) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd012768.pub2 · Cited by 245

Multiple Imputation of Missing Data for Multilevel Models: Simulations and Recommendations

Grund, S., Lüdtke, O., & Robitzsch, A. (2018) · Organizational Research Methods · doi:10.1177/1094428117703686 · Cited by 224

Psychological treatments for post-traumatic stress disorder in adults: a network meta-analysis

Mavranezouli, I., Megnin-Viggars, O., Daly, C., Dias, S., Welton, N. J., Stockton, S., Bhutani, G., Grey, N., Leach, J., Greenberg, N., et al. (2020) · Psychological Medicine · doi:10.1017/s0033291720000070 · Cited by 212

Meta-analysis of randomised controlled trials of oral mandibular advancement devices and continuous positive airway pressure for obstructive sleep apnoea-hypopnoea

Sharples, L. D., Clutterbuck-James, A. L., Glover, M. J., Bennett, M. S., Chadwick, R., Pittman, M. A., & Quinnell, T. G. (2016) · Sleep Medicine Reviews · doi:10.1016/j.smrv.2015.05.003 · Cited by 202

Was Dinosaurian Physiology Inherited by Birds? Reconciling Slow Growth in Archaeopteryx

Erickson, G. M., Rauhut, O. W. M., Zhou, Z., Turner, A. H., Inouye, B. D., Hu, D., & Norell, M. A. (2009) · PLoS ONE · doi:10.1371/journal.pone.0007390 · Cited by 195

Modern departures in fire severity and area vary by forest type, Sierra Nevada and southern Cascades, California, USA

Mallek, C., Safford, H., Viers, J., & Miller, J. (2013) · Ecosphere · doi:10.1890/es13-00217.1 · Cited by 183

Combining randomized and non-randomized evidence in network meta-analysis

Efthimiou, O., Mavridis, D., Debray, T. P. A., Samara, M., Belger, M., Siontis, G. C. M., Leucht, S., Salanti, G., & 4, O. B. O. G. W. P. (2017) · Statistics in Medicine · doi:10.1002/sim.7223 · Cited by 183

Case Management for Depression by Health Care Assistants in Small Primary Care Practices: A Cluster Randomized Trial

Gensichen, J., von Korff, M., Peitz, M., Muth, C., Beyer, M., Güthlin, C., Torge, M., Petersen, J. J., Rosemann, T., König, J., et al. (2009) · Annals of Internal Medicine · doi:10.7326/0003-4819-151-6-200909150-00001 · Cited by 181

Impact of Different Training Modalities on Anthropometric and Metabolic Characteristics in Overweight/Obese Subjects: A Systematic Review and Network Meta-Analysis

Schwingshackl, L., Dias, S., Strasser, B., & Hoffmann, G. (2013) · PLoS ONE · doi:10.1371/journal.pone.0082853 · Cited by 180

Research review: psychological and psychosocial treatments for children and young people with post-traumatic stress disorder: a network meta-analysis

Mavranezouli, I., Megnin‐Viggars, O., Daly, C., Dias, S., Stockton, S., Meiser‐Stedman, R., Trickey, D., & Pilling, S. (2020) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13094 · Cited by 172

Effects of interest–major congruence, motivation, and academic performance on timely degree attainment.

Allen, J., & Robbins, S. (2010) · Journal of Counseling Psychology · doi:10.1037/a0017267 · Cited by 166

Home telemonitoring or structured telephone support programmes after recent discharge in patients with heart failure: systematic review and economic evaluation

Pandor, A., Thokala, P., Gomersall, T., Baalbaki, H., Stevens, J., Wang, J., Wong, R., Brennan, A., & Fitzgerald, P. (2013) · Health Technol Assess · doi:10.3310/hta17320 · Cited by 159

Independent contrasts and PGLS regression estimators are equivalent

Blomberg, S. P., Lefevre, J. G., Wells, J. A., & Waterhouse, M. (2012) · Systematic Biology · doi:10.1093/sysbio/syr118 · Cited by 158

Bayesian Estimation of the Performance of Using Clinical Observations and Harvest Lung Lesions for Diagnosing Bovine Respiratory Disease in Post-weaned Beef Calves

White, B. J., & Renter, D. G. (2009) · Journal of Veterinary Diagnostic Investigation · doi:10.1177/104063870902100405 · Cited by 156

A systematic review, evidence synthesis and meta-analysis of quantitative and qualitative studies evaluating the clinical effectiveness, the cost-effectiveness, safety and acceptability of interventions to prevent postnatal depression

Morrell, C. J., Sutcliffe, P., Booth, A., Stevens, J., Scope, A., Stevenson, M., Harvey, R., Bessey, A., Cantrell, A., Dennis, C.-L., et al. (2016) · Health Technology Assessment · doi:10.3310/hta20370 · Cited by 155

Developmental changes in cerebral grey and white matter volume from infancy to adulthood

Groeschel, S., Vollmer, B., King, M. D., & Connelly, A. (2010) · International Journal of Developmental Neuroscience · doi:10.1016/j.ijdevneu.2010.06.004 · Cited by 147

Comparative effectiveness of different forms of telemedicine for individuals with heart failure (HF): a systematic review and network meta-analysis.

Kotb, A., Cameron, C., Hsieh, S., & Wells, G. (2015) · PLOS ONE · doi:10.1371/journal.pone.0118681 · Cited by 149

How to quantify support for and against the null hypothesis: A flexible WinBUGS implementation of a default Bayesian t test

Wetzels, R., Raaijmakers, J. G. W., Jakab, E., & Wagenmakers, E.-J. (2009) · Psychonomic Bulletin & Review · doi:10.3758/pbr.16.4.752 · Cited by 143

Randomized Clinical Trial of an Emergency Department Observation Syncope Protocol Versus Routine Inpatient Admission

Sun, B. C., McCreath, H., Liang, L.-J., Bohan, S., Baugh, C., Ragsdale, L., Henderson, S. O., Clark, C., Bastani, A., Keeler, E., et al. (2014) · Annals of Emergency Medicine · doi:10.1016/j.annemergmed.2013.10.029 · Cited by 114

A Meta-Analysis of Executive Dysfunction and Antidepressant Treatment Response in Late-Life Depression

Pimontel, M. A., Rindskopf, D., Rutherford, B. R., Brown, P. J., Roose, S. P., & Sneed, J. R. (2016) · The American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2015.05.010 · Cited by 110

Must psychologists change the way they analyze their data?

Bem, D. J., Utts, J., & Johnson, W. O. (2011) · Journal of Personality and Social Psychology · doi:10.1037/a0024777 · Cited by 105

Probabilistic reinforcement learning in adults with autism spectrum disorders

Solomon, M., Smith, A. C., Frank, M. J., Ly, S., & Carter, C. S. (2011) · Autism Research · doi:10.1002/aur.177 · Cited by 97

Diet of the prehistoric population of Rapa Nui (Easter Island, Chile) shows environmental adaptation and resilience

Jarman, C. L., Larsen, T., Hunt, T., Lipo, C., Solsvik, R., Wallsgrove, N., Ka'apu‐Lyons, C., Close, H. G., & Popp, B. N. (2017) · American Journal of Physical Anthropology · doi:10.1002/ajpa.23273 · Cited by 94

Therapist variation within randomised trials of psychotherapy: implications for precision, internal and external validity

Walwyn, R., & Roberts, C. (2010) · Statistical Methods in Medical Research · doi:10.1177/0962280209105017 · Cited by 93

Defining Falciparum-Malaria-Attributable Severe Febrile Illness in Moderate-to-High Transmission Settings on the Basis of Plasma PfHRP2 Concentration

Hendriksen, I. C. E., White, L. J., Veenemans, J., Mtove, G., Woodrow, C., Amos, B., Saiwaew, S., Gesase, S., Nadjm, B., Silamut, K., et al. (2013) · The Journal of Infectious Diseases · doi:10.1093/infdis/jis675 · Cited by 93

State Firearm Laws and Interstate Firearm Deaths From Homicide and Suicide in the United States: A Cross-sectional Analysis of Data by County

Kaufman, E. J., Morrison, C. N., Branas, C. C., & Wiebe, D. J. (2018) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2018.0190 · Cited by 91

Increased Risk of Autism Spectrum Disorders in Children Born to Women With Systemic Lupus Erythematosus: Results From a Large Population‐Based Cohort

Vinet, É., Pineau, C. A., Clarke, A. E., Scott, S., Fombonne, É., Joseph, L., Platt, R. W., & Bernatsky, S. (2015) · Arthritis & Rheumatology · doi:10.1002/art.39320 · Cited by 81

Timing of Coronary Invasive Strategy in Non–ST-Segment Elevation Acute Coronary Syndromes and Clinical Outcomes

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Spatial and Temporal Patterns in Concentrations of Perfluorinated Compounds in Bald Eagle Nestlings in the Upper Midwestern United States

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