| Year |
Citation |
Score |
| 2020 |
Aczel B, Hoekstra R, Gelman A, Wagenmakers EJ, Klugkist IG, Rouder JN, Vandekerckhove J, Lee MD, Morey RD, Vanpaemel W, Dienes Z, van Ravenzwaaij D. Discussion points for Bayesian inference. Nature Human Behaviour. PMID 31988442 DOI: 10.1038/S41562-019-0807-Z |
0.326 |
|
| 2020 |
Gao Y, Kennedy L, Simpson D, Gelman A. Improving Multilevel Regression and Poststratification with Structured Priors Bayesian Analysis. DOI: 10.1214/20-Ba1223 |
0.389 |
|
| 2020 |
Gelman A, Carpenter B. Bayesian analysis of tests with unknown specificity and sensitivity Journal of the Royal Statistical Society Series C-Applied Statistics. DOI: 10.1111/Rssc.12435 |
0.337 |
|
| 2020 |
Gelman A, Guzey A. Statistics as Squid Ink: How Prominent Researchers Can Get Away with Misrepresenting Data Chance. 33: 25-27. DOI: 10.1080/09332480.2020.1754069 |
0.303 |
|
| 2020 |
Ghitza Y, Gelman A. Voter Registration Databases and MRP: Toward the Use of Large-Scale Databases in Public Opinion Research Political Analysis. 1-25. DOI: 10.1017/Pan.2020.3 |
0.742 |
|
| 2019 |
Morris M, Wheeler-Martin K, Simpson D, Mooney SJ, Gelman A, DiMaggio C. Bayesian hierarchical spatial models: Implementing the Besag York Mollié model in stan. Spatial and Spatio-Temporal Epidemiology. 31: 100301. PMID 31677766 DOI: 10.1016/J.Sste.2019.100301 |
0.328 |
|
| 2019 |
Gelman A. When we make recommendations for scientific practice, we are (at best) acting as social scientists. European Journal of Clinical Investigation. e13165. PMID 31421055 DOI: 10.1111/Eci.13165 |
0.321 |
|
| 2019 |
Gelman A. Of chaos, storms and forking paths: the principles of uncertainty. Nature. 569: 628-629. PMID 31142859 DOI: 10.1038/D41586-019-01680-Y |
0.319 |
|
| 2019 |
Gabry J, Simpson D, Vehtari A, Betancourt M, Gelman A. Visualization in Bayesian workflow Journal of the Royal Statistical Society Series a-Statistics in Society. 182: 389-402. DOI: 10.1111/Rssa.12378 |
0.326 |
|
| 2019 |
van Dongen NNN, van Doorn JB, Gronau QF, van Ravenzwaaij D, Hoekstra R, Haucke MN, Lakens D, Hennig C, Morey RD, Homer S, Gelman A, Sprenger J, Wagenmakers E. Multiple Perspectives on Inference for Two Simple Statistical Scenarios The American Statistician. 73: 328-339. DOI: 10.1080/00031305.2019.1565553 |
0.378 |
|
| 2019 |
Gelman A, Goodrich B, Gabry J, Vehtari A. R-squared for Bayesian regression models The American Statistician. 73: 307-309. DOI: 10.1080/00031305.2018.1549100 |
0.301 |
|
| 2018 |
Mitchell S, Gelman A, Ross R, Chen J, Bari S, Huynh UK, Harris MW, Sachs SE, Stuart EA, Feller A, Makela S, Zaslavsky AM, McClellan L, Ohemeng-Dapaah S, Namakula P, et al. The Millennium Villages Project: a retrospective, observational, endline evaluation. The Lancet. Global Health. 6: e500-e513. PMID 29653625 DOI: 10.1016/S2214-109X(18)30065-2 |
0.438 |
|
| 2018 |
Weber S, Gelman A, Lee D, Betancourt M, Vehtari A, Racine-Poon A. Bayesian aggregation of average data: An application in drug development The Annals of Applied Statistics. 12: 1583-1604. DOI: 10.1214/17-Aoas1122 |
0.331 |
|
| 2018 |
Gelman A, Imbens G. Why High-Order Polynomials Should Not Be Used in Regression Discontinuity Designs Journal of Business & Economic Statistics. 37: 447-456. DOI: 10.1080/07350015.2017.1366909 |
0.354 |
|
| 2018 |
Shirani-Mehr H, Rothschild D, Goel S, Gelman A. Disentangling Bias and Variance in Election Polls Journal of the American Statistical Association. 113: 607-614. DOI: 10.1080/01621459.2018.1448823 |
0.306 |
|
| 2018 |
Vasishth S, Mertzen D, Jäger LA, Gelman A. The statistical significance filter leads to overoptimistic expectations of replicability Journal of Memory and Language. 103: 151-175. DOI: 10.1016/J.Jml.2018.07.004 |
0.316 |
|
| 2017 |
Gelman A. The Failure of Null Hypothesis Significance Testing When Studying Incremental Changes, and What to Do About It. Personality & Social Psychology Bulletin. 146167217729162. PMID 28914154 DOI: 10.1177/0146167217729162 |
0.321 |
|
| 2017 |
Marsman M, Schönbrodt FD, Morey RD, Yao Y, Gelman A, Wagenmakers EJ. A Bayesian bird's eye view of 'Replications of important results in social psychology'. Royal Society Open Science. 4: 160426. PMID 28280547 DOI: 10.1098/Rsos.160426 |
0.353 |
|
| 2017 |
Loken E, Gelman A. Measurement error and the replication crisis. Science (New York, N.Y.). 355: 584-585. PMID 28183939 DOI: 10.1126/Science.Aal3618 |
0.332 |
|
| 2017 |
Carpenter B, Gelman A, Hoffman MD, Lee D, Goodrich B, Betancourt M, Brubaker M, Guo J, Li P, Riddell A. Stan: A Probabilistic Programming Language Journal of Statistical Software. 76. DOI: 10.18637/Jss.V076.I01 |
0.332 |
|
| 2017 |
Grant RL, Furr DC, Carpenter B, Gelman A. Fitting Bayesian item response models in Stata and Stan Stata Journal. 17: 343-357. DOI: 10.1177/1536867X1701700206 |
0.339 |
|
| 2017 |
Grant RL, Carpenter B, Furr DC, Gelman A. Introducing the StataStan interface for fast, complex Bayesian modeling using Stan Stata Journal. 17: 330-342. DOI: 10.1177/1536867X1701700205 |
0.305 |
|
| 2017 |
Gelman A. Ethics and Statistics: Honesty and Transparency Are Not Enough Chance. 30: 37-39. DOI: 10.1080/09332480.2017.1302720 |
0.309 |
|
| 2017 |
Vehtari A, Gelman A, Gabry J. Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC Statistics and Computing. 27: 1413-1432. DOI: 10.1007/S11222-016-9696-4 |
0.36 |
|
| 2016 |
Steegen S, Tuerlinckx F, Gelman A, Vanpaemel W. Increasing Transparency Through a Multiverse Analysis. Perspectives On Psychological Science : a Journal of the Association For Psychological Science. 11: 702-712. PMID 27694465 DOI: 10.1177/1745691616658637 |
0.328 |
|
| 2016 |
Gelman A, Goel S, Rivers D, Rothschild D. The mythical swing voter Quarterly Journal of Political Science. 11: 103-130. DOI: 10.1561/100.00015031 |
0.314 |
|
| 2016 |
Schofield MR, Barker RJ, Gelman A, Cook ER, Briffa KR. A Model-Based Approach to Climate Reconstruction Using Tree-Ring Data Journal of the American Statistical Association. 111: 93-106. DOI: 10.1080/01621459.2015.1110524 |
0.313 |
|
| 2015 |
Chen Q, Gelman A, Tracy M, Norris FH, Galea S. Incorporating the sampling design in weighting adjustments for panel attrition. Statistics in Medicine. PMID 26239405 DOI: 10.1002/Sim.6618 |
0.301 |
|
| 2015 |
Wang W, Gelman A. Difficulty of selecting among multilevel models using predictive accuracy Statistics and Its Interface. 8: 153-160. DOI: 10.4310/Sii.2015.V8.N2.A3 |
0.334 |
|
| 2015 |
Chung Y, Gelman A, Rabe-Hesketh S, Liu J, Dorie V. Weakly Informative Prior for Point Estimation of Covariance Matrices in Hierarchical Models Journal of Educational and Behavioral Statistics. 40: 136-157. DOI: 10.3102/1076998615570945 |
0.777 |
|
| 2015 |
Si Y, Pillai NS, Gelman A. Bayesian nonparametric weighted sampling inference Bayesian Analysis. 10: 605-625. DOI: 10.1214/14-Ba924 |
0.329 |
|
| 2015 |
Gelman A, Zelizer A. Evidence on the deleterious impact of sustained use of polynomial regression on causal inference Research & Politics. 2: 205316801556983. DOI: 10.1177/2053168015569830 |
0.397 |
|
| 2015 |
Gelman A. The Connection Between Varying Treatment Effects and the Crisis of Unreplicable Research: A Bayesian Perspective Journal of Management. 41: 632-643. DOI: 10.1177/0149206314525208 |
0.326 |
|
| 2015 |
Shirley KE, Gelman A. Hierarchical models for estimating state and demographic trends in US death penalty public opinion Journal of the Royal Statistical Society. Series a: Statistics in Society. 178: 1-28. DOI: 10.1111/Rssa.12052 |
0.366 |
|
| 2015 |
Gelman A. Working through some issues Significance. 12: 33-35. DOI: 10.1111/J.1740-9713.2015.00828.X |
0.315 |
|
| 2015 |
Gelman A, Madigan D. Ethics and Statistics: How is Ethics Like Logistic Regression? Ethics decisions, like statistical inferences, are informative only if they're not too easy or too hard Chance. 28: 31-33. DOI: 10.1080/09332480.2015.1042734 |
0.307 |
|
| 2015 |
Liu Y, Gelman A, Zheng T. Simulation-efficient shortest probability intervals Statistics and Computing. 25: 809-819. DOI: 10.1007/S11222-015-9563-8 |
0.313 |
|
| 2014 |
Gelman A, Carlin J. Beyond Power Calculations: Assessing Type S (Sign) and Type M (Magnitude) Errors. Perspectives On Psychological Science : a Journal of the Association For Psychological Science. 9: 641-51. PMID 26186114 DOI: 10.1177/1745691614551642 |
0.327 |
|
| 2014 |
Gelman A, Loken E. The statistical Crisis in science American Scientist. 102: 460-465. DOI: 10.1511/2014.111.460 |
0.342 |
|
| 2014 |
Gelman A. How Bayesian analysis cracked the red-state, blue-state problem Statistical Science. 29: 26-35. DOI: 10.1214/13-Sts458 |
0.359 |
|
| 2014 |
Gelman A, Basbøll T. When Do Stories Work? Evidence and Illustration in the Social Sciences Sociological Methods and Research. 43: 547-570. DOI: 10.1177/0049124114526377 |
0.314 |
|
| 2014 |
Liu J, Gelman A, Hill J, Su YS, Kropko J. On the stationary distribution of iterative imputations Biometrika. 101: 155-173. DOI: 10.1093/Biomet/Ast044 |
0.365 |
|
| 2014 |
Wang W, Rothschild D, Goel S, Gelman A. Forecasting elections with non-representative polls International Journal of Forecasting. DOI: 10.1016/J.Ijforecast.2014.06.001 |
0.362 |
|
| 2014 |
Gelman A, Hwang J, Vehtari A. Understanding predictive information criteria for Bayesian models Statistics and Computing. 24: 997-1016. DOI: 10.1007/S11222-013-9416-2 |
0.332 |
|
| 2013 |
Chung Y, Rabe-Hesketh S, Dorie V, Gelman A, Liu J. A nondegenerate penalized likelihood estimator for variance parameters in multilevel models. Psychometrika. 78: 685-709. PMID 24092484 DOI: 10.1007/S11336-013-9328-2 |
0.774 |
|
| 2013 |
Gelman A, Shalizi C. Rejoinder to discussion of 'Philosophy and the practice of Bayesian statistics'. The British Journal of Mathematical and Statistical Psychology. 66: 76-80. PMID 23050946 DOI: 10.1111/J.2044-8317.2012.02066.X |
0.377 |
|
| 2013 |
Gelman A, Shalizi CR. Philosophy and the practice of Bayesian statistics. The British Journal of Mathematical and Statistical Psychology. 66: 8-38. PMID 22364575 DOI: 10.1111/J.2044-8317.2011.02037.X |
0.373 |
|
| 2013 |
Gelman A, Robert CP, Rousseau J. Inherent difficulties of non-Bayesian likelihood-based inference, as revealed by an examination of a recent book by Aitkin Statistics & Risk Modeling. 30. DOI: 10.1524/Strm.2013.1113 |
0.382 |
|
| 2013 |
Thomas AC, Gelman A, King G, Katz JN. Estimating Partisan Bias of the Electoral College Under Proposed Changes in Elector Apportionment Statistics, Politics and Policy. 4: 1-13. DOI: 10.1515/Spp-2012-0001 |
0.305 |
|
| 2013 |
Gelman A. Two simple examples for understanding posterior p-values whose distributions are far from unform Electronic Journal of Statistics. 7: 2595-2602. DOI: 10.1214/13-Ejs854 |
0.311 |
|
| 2013 |
Ghitza Y, Gelman A. Deep interactions with MRP: Election turnout and voting patterns among small electoral subgroups American Journal of Political Science. 57: 762-776. DOI: 10.1111/Ajps.12004 |
0.779 |
|
| 2013 |
Gelman A, Unwin A. Infovis and statistical graphics: Different goals, different looks Journal of Computational and Graphical Statistics. 22: 2-28. DOI: 10.1080/10618600.2012.761137 |
0.38 |
|
| 2013 |
Gelman A. Ethics and Statistics: It's Too Hard to Publish Criticisms and Obtain Data for Republication Chance. 26: 49-52. DOI: 10.1080/09332480.2013.845455 |
0.319 |
|
| 2013 |
Gelman A, Palko M. Ethics and Statistics: The War on Data Chance. 26: 57-60. DOI: 10.1080/09332480.2013.772395 |
0.329 |
|
| 2013 |
Gelman A, Robert CP. "Not only defended but also applied": The perceived absurdity of Bayesian inference American Statistician. 67: 1-5. DOI: 10.1080/00031305.2013.760987 |
0.361 |
|
| 2013 |
Gelman A, Robert CP. Rejoinder: The anti-Bayesian moment and its passing American Statistician. 67: 16-17. DOI: 10.1080/00031305.2012.752409 |
0.322 |
|
| 2012 |
Feller A, Gelman A, Shor B. Red state/blue state divisions in the 2012 presidential election Forum (Germany). 10: 127-131. DOI: 10.1515/Forum-2013-0014 |
0.306 |
|
| 2012 |
Kaplan N, Park DK, Gelman A. Polls and ElectionsUnderstanding Persuasion and Activation in Presidential Campaigns: The Random Walk and Mean Reversion Models Presidential Studies Quarterly. 42: 843-866. DOI: 10.1111/J.1741-5705.2012.04021.X |
0.344 |
|
| 2012 |
Gelman A, Silver N, Edlin A. What is the probability your vote will make a difference? Economic Inquiry. 50: 321-326. DOI: 10.1111/J.1465-7295.2010.00272.X |
0.309 |
|
| 2012 |
Gelman A. Ethics and Statistics: Ethics and the Statistical Use of Prior Information Chance. 25: 52-54. DOI: 10.1080/09332480.2012.752294 |
0.32 |
|
| 2012 |
Brooks S, Gelman A, Jones G, Meng X. Handbook of Markov Chain Monte Carlo: Hardcover: 619 pages Publisher: Chapman and Hall/CRC Press (first edition, May 2011) Language: English ISBN-10: 1420079417 Chance. 25: 53-55. DOI: 10.1080/09332480.2012.668472 |
0.476 |
|
| 2012 |
Gross JH, Shalizi CR, Gelman A. Does the US Media Have a Liberal Bias? Perspectives On Politics. 10: 775-779. DOI: 10.1017/S1537592712001387 |
0.317 |
|
| 2011 |
Gelman A. Why tables are really much better than graphs Journal of Computational and Graphical Statistics. 20: 3-7. DOI: 10.1198/Jcgs.2011.09166 |
0.376 |
|
| 2011 |
Gelman A. Causality and statistical learning American Journal of Sociology. 117: 955-966. DOI: 10.1086/662659 |
0.308 |
|
| 2011 |
Gelman A. Ethics and Statistics Chance. 24: 51-53. DOI: 10.1080/09332480.2011.10739888 |
0.342 |
|
| 2010 |
Gelman A, Silver N. What do we know at 7 PM on election night? Mathematics Magazine. 83: 258-266. DOI: 10.4169/002557010X521787 |
0.352 |
|
| 2010 |
Gelman A, Lee D, Ghitza Y. Public Opinion on Health Care Reform The Forum. 8. DOI: 10.2202/1540-8884.1355 |
0.752 |
|
| 2010 |
Gelman A. Bayesian statistics then and now Statistical Science. 25: 162-165. DOI: 10.1214/10-Sts308B |
0.36 |
|
| 2010 |
Lock K, Gelman A. Bayesian combination of state polls and election forecasts Political Analysis. 18: 337-348. DOI: 10.1093/Pan/Mpq002 |
0.777 |
|
| 2010 |
Gelman A, Leenen I, Mechelen IV, Boeck PD, Poblome J. Bridges between Deterministic and Probabilistic Models for Binary Data Statistical Methodology. 7: 187-209. DOI: 10.1016/J.Stamet.2009.08.005 |
0.341 |
|
| 2009 |
Gelman A. Discussion of the article "website morphing" Marketing Science. 28: 226. DOI: 10.1287/Mksc.1080.0476 |
0.337 |
|
| 2008 |
Gelman A. Scaling regression inputs by dividing by two standard deviations. Statistics in Medicine. 27: 2865-73. PMID 17960576 DOI: 10.1002/Sim.3107 |
0.349 |
|
| 2008 |
Gelman A. Objections to Bayesian statistics Bayesian Analysis. 3: 445-450. DOI: 10.1214/08-Ba318 |
0.334 |
|
| 2008 |
Gelman A, Jakulin A, Pittau MG, Su Y. A weakly informative default prior distribution for logistic and other regression models The Annals of Applied Statistics. 2: 1360-1383. DOI: 10.1214/08-Aoas191 |
0.382 |
|
| 2008 |
Gelman A, Van Dyk DA, Huang Z, Boscardin WJ. Using redundant parameterizations to fit hierarchical models Journal of Computational and Graphical Statistics. 17: 95-122. DOI: 10.1198/106186008X287337 |
0.404 |
|
| 2008 |
Gelman A, Huang Z. Estimating Incumbency Advantage and Its Variation, as an Example of a Before–After Study Journal of the American Statistical Association. 103: 437-446. DOI: 10.1198/016214507000000626 |
0.511 |
|
| 2008 |
Gelman A. Teaching bayes to graduate students in political science, sociology, public health, education, economics, .. American Statistician. 62: 202-205. DOI: 10.1198/000313008X330829 |
0.306 |
|
| 2008 |
Abayomi K, Gelman A, Levy M. Diagnostics for multivariate imputations Journal of the Royal Statistical Society. Series C: Applied Statistics. 57: 273-291. DOI: 10.1111/J.1467-9876.2007.00613.X |
0.355 |
|
| 2007 |
Reilly C, Gelman A. Weighted classical variogram estimation for data with clustering Technometrics. 49: 184-194. DOI: 10.1198/004017006000000282 |
0.553 |
|
| 2007 |
Gelman A, Pardoe I. Average predictive comparisons for models with nonlinearity, interactions, and variance components Sociological Methodology. 37: 23-51. DOI: 10.1111/J.1467-9531.2007.00181.X |
0.345 |
|
| 2007 |
Rogard E, Gelman A, Lu H. Evaluation of multilevel decision trees Journal of Statistical Planning and Inference. 137: 1151-1160. DOI: 10.1016/J.Jspi.2006.01.011 |
0.463 |
|
| 2007 |
Kerman J, Gelman A. Manipulating and summarizing posterior simulations using random variable objects Statistics and Computing. 17: 235-244. DOI: 10.1007/S11222-007-9020-4 |
0.76 |
|
| 2006 |
Gelman A. Prior distributions for variance parameters in hierarchical models (Comment on Article by Browne and Draper) Bayesian Analysis. 1: 515-534. DOI: 10.1214/06-Ba117A |
0.328 |
|
| 2006 |
Fan Y, Brooks SP, Gelman A. Output assessment for monte carlo simulations via the score statistic Journal of Computational and Graphical Statistics. 15: 178-206. DOI: 10.1198/106186006X96908 |
0.358 |
|
| 2006 |
Cook SR, Gelman A, Rubin DB. Validation of software for Bayesian models using posterior quantiles Journal of Computational and Graphical Statistics. 15: 675-692. DOI: 10.1198/106186006X136976 |
0.528 |
|
| 2006 |
Gelman A. Multilevel (hierarchical) modeling: What It can and cannot do Technometrics. 48: 432-435. DOI: 10.1198/004017005000000661 |
0.347 |
|
| 2006 |
Gelman A, Pardoe I. Bayesian measures of explained variance and pooling in multilevel (hierarchical) models Technometrics. 48: 241-251. DOI: 10.1198/004017005000000517 |
0.364 |
|
| 2006 |
Gelman A, Stern H. The difference between "significant" and "not significant" is not itself statistically significant American Statistician. 60: 328-331. DOI: 10.1198/000313006X152649 |
0.333 |
|
| 2006 |
Gelman A. The boxer, the wrestler, and the coin flip: A paradox of Robust Bayesian inference and belief functions American Statistician. 60: 146-150. DOI: 10.1198/000313006X106190 |
0.349 |
|
| 2005 |
Gelman A, Van Mechelen I, Verbeke G, Heitjan DF, Meulders M. Multiple imputation for model checking: completed-data plots with missing and latent data. Biometrics. 61: 74-85. PMID 15737080 DOI: 10.1111/J.0006-341X.2005.031010.X |
0.68 |
|
| 2005 |
Gelman A. Analysis of variance—why it is more important than ever The Annals of Statistics. 33: 1-53. DOI: 10.1214/009053604000001048 |
0.367 |
|
| 2005 |
Gelman A. Two-stage regression and multilevel modeling: A commentary Political Analysis. 13: 459-461. DOI: 10.1093/Pan/Mpi032 |
0.368 |
|
| 2005 |
Bafumi J, Gelman A, Park DK, Kaplan N. Practical issues in implementing and understanding Bayesian ideal point estimation Political Analysis. 13: 171-187. DOI: 10.1093/Pan/Mpi010 |
0.403 |
|
| 2004 |
Gelman A, Trevisani M, Lu H, van Geen A. Direct data manipulation for local decision analysis as applied to the problem of arsenic in drinking water from tube wells in Bangladesh. Risk Analysis : An Official Publication of the Society For Risk Analysis. 24: 1597-612. PMID 15660615 DOI: 10.1111/J.0272-4332.2004.00553.X |
0.505 |
|
| 2004 |
Reilly C, Price P, Gelman A, Sandgathe SA. Using image and curve registration for measuring the goodness of fit of spatial and temporal predictions. Biometrics. 60: 954-64. PMID 15606416 DOI: 10.1111/J.0006-341X.2004.00251.X |
0.51 |
|
| 2004 |
Gelman A, Chew GL, Shnaidman M. Bayesian analysis of serial dilution assays. Biometrics. 60: 407-17. PMID 15180666 DOI: 10.1111/J.0006-341X.2004.00185.X |
0.357 |
|
| 2004 |
Gelman A. Exploratory data analysis for complex models Journal of Computational and Graphical Statistics. 13: 755-779. DOI: 10.1198/106186004X11435 |
0.386 |
|
| 2004 |
Gelman A. Parameterization and Bayesian modeling Journal of the American Statistical Association. 99: 537-545. DOI: 10.1198/016214504000000458 |
0.355 |
|
| 2004 |
Park DK, Gelman A, Bafumi J. Bayesian multilevel estimation with poststratification: State-level estimates from national polls Political Analysis. 12: 375-385. DOI: 10.1093/Pan/Mph024 |
0.403 |
|
| 2004 |
Gelman A, Katz JN, Bafumi J. Standard voting power indexes do not work: An empirical analysis British Journal of Political Science. 34: 657-674. DOI: 10.1017/S0007123404000237 |
0.315 |
|
| 2003 |
Gelman A, Stevens M, Chan V. Regression Modeling and Meta-Analysis for Decision Making Journal of Business & Economic Statistics. 21: 213-225. DOI: 10.1198/073500103288618909 |
0.346 |
|
| 2002 |
Gelman A, Katz JN, Tuerlinckx F. The mathematics and statistics of voting power Statistical Science. 17: 420-435. DOI: 10.1214/Ss/1049993201 |
0.327 |
|
| 2002 |
Gelman A, Pasarica C, Dodhia R. Let's practice what we preach: Turning tables into graphs American Statistician. 56: 121-130. DOI: 10.1198/000313002317572790 |
0.737 |
|
| 2002 |
Gelman A, Nolan D. A Probability Model for Golf Putting Teaching Statistics. 24: 93-95. DOI: 10.1111/1467-9639.00097 |
0.323 |
|
| 2001 |
Carlin JB, Wolfe R, Brown CH, Gelman A. A case study on the choice, interpretation and checking of multilevel models for longitudinal binary outcomes. Biostatistics (Oxford, England). 2: 397-416. PMID 12933632 DOI: 10.1093/Biostatistics/2.4.397 |
0.393 |
|
| 2001 |
Meulders M, De Boeck P, Van Mechelen I, Gelman A, Maris E. Bayesian inference with probability matrix decomposition models Journal of Educational and Behavioral Statistics. 26: 153-179. DOI: 10.3102/10769986026002153 |
0.373 |
|
| 2001 |
Reilly C, Gelman A, Katz J. Poststratification Without Population Level Information on the Poststratifying Variable With Application to Political Polling Journal of the American Statistical Association. 96: 1-11. DOI: 10.1198/016214501750332640 |
0.567 |
|
| 2001 |
Gelman A, Park DK, Ansolabehere S, Price PN, Minnite LC. Models, assumptions and model checking in ecological regressions Journal of the Royal Statistical Society: Series a (Statistics in Society). 164: 101-118. DOI: 10.1111/1467-985X.00190 |
0.375 |
|
| 2000 |
Gelman A, Goegebeur Y, Tuerlinckx F, Van Mechelen I. Diagnostic checks for discrete data regression models using posterior predictive simulations Journal of the Royal Statistical Society: Series C (Applied Statistics). 49: 247-268. DOI: 10.1111/1467-9876.00190 |
0.381 |
|
| 2000 |
Leenen I, Mechelen IV, Gelman A. Bayesian probabilistic extensions of a deterministic classification model Computational Statistics. 15: 355-371. DOI: 10.1007/S001800000039 |
0.361 |
|
| 1999 |
GELMAN A, RUBIN DB. Evaluating and Using Statistical Methods in the Social Sciences Sociological Methods & Research. 27: 403-410. DOI: 10.1177/0049124199027003004 |
0.474 |
|
| 1998 |
Gelman A, King G, Boscardin WJ. Estimating the probability of events that have never occurred : When is your vote decisive? Journal of the American Statistical Association. 93: 1-9. DOI: 10.2307/2669597 |
0.402 |
|
| 1998 |
Gelman A, Meng X. Simulating Normalizing Constants: From Importance Sampling to Bridge Sampling to Path Sampling Statistical Science. 13: 163-185. DOI: 10.1214/Ss/1028905934 |
0.54 |
|
| 1998 |
Gelman A, King G, Liu C. Not Asked and Not Answered: Multiple Imputation for Multiple Surveys Journal of the American Statistical Association. 93: 846-857. DOI: 10.1080/01621459.1998.10473737 |
0.363 |
|
| 1998 |
Kass RE, Carlin BP, Gelman A, Neal RM. Markov Chain Monte Carlo in Practice: A Roundtable Discussion American Statistician. 52: 93-100. DOI: 10.1080/00031305.1998.10480547 |
0.347 |
|
| 1997 |
Halloran ME, Gelman A, Carlin JB, Stern HS, Rubin DB, Carlin BP, Louis TA. Bayesian Data Analysis. Journal of the American Statistical Association. 92: 1640. DOI: 10.2307/2965436 |
0.502 |
|
| 1996 |
Gelman A, Rubin DB. Markov chain Monte Carlo methods in biostatistics. Statistical Methods in Medical Research. 5: 339-55. PMID 9004377 DOI: 10.1177/096228029600500402 |
0.524 |
|
| 1996 |
Bois FY, Gelman A, Jiang J, Maszle DR, Zeise L, Alexeef G. Population toxicokinetics of tetrachloroethylene. Archives of Toxicology. 70: 347-355. PMID 8975633 DOI: 10.1007/S002040050284 |
0.337 |
|
| 1996 |
Price PN, Nero AV, Gelman A. Bayesian prediction of mean indoor radon concentrations for Minnesota counties Health Physics. 71: 922-936. PMID 8919076 DOI: 10.1097/00004032-199612000-00009 |
0.323 |
|
| 1996 |
Gelman A, Bois F, Jiang J. Physiological Pharmacokinetic Analysis Using Population Modeling and Informative Prior Distributions Journal of the American Statistical Association. 91: 1400-1412. DOI: 10.1080/01621459.1996.10476708 |
0.343 |
|
| 1995 |
Gelman A, Rubin DB. Avoiding Model Selection in Bayesian Social Research Sociological Methodology. 25: 165. DOI: 10.2307/271064 |
0.555 |
|
| 1995 |
Voss DS, Gelman A, King G. A Review: Preelection Survey Methodology: Details From Eight Polling Organizations, 1988 and 1992 Public Opinion Quarterly. 59: 98. DOI: 10.1086/269461 |
0.313 |
|
| 1995 |
Gelman A. Method of moments using monte carlo simulation Journal of Computational and Graphical Statistics. 4: 36-54. DOI: 10.1080/10618600.1995.10474664 |
0.376 |
|
| 1994 |
Gelman A, King G. Enhancing democracy through legislative redistricting American Political Science Review. 88: 541-559. DOI: 10.2307/2944794 |
0.327 |
|
| 1994 |
Gelman A, King G. A Unified Method of Evaluating Electoral Systems and Redistricting Plans American Journal of Political Science. 38: 514. DOI: 10.2307/2111417 |
0.376 |
|
| 1993 |
Gelman A, King G. Why Are American Presidential Election Campaign Polls So Variable When Votes Are So Predictable? British Journal of Political Science. 23: 409-451. DOI: 10.1017/S0007123400006682 |
0.309 |
|
| 1992 |
Gelman A, Rubin DB. Rejoinder: Replication without contrition Statistical Science. 7: 503-511. DOI: 10.1214/Ss/1177011148 |
0.425 |
|
| 1992 |
Gelman A, Rubin DB. Inference from iterative simulation using multiple sequences Statistical Science. 7: 457-472. DOI: 10.1214/Ss/1177011136 |
0.548 |
|
| 1991 |
Gelman A, Meng X. A Note on Bivariate Distributions That are Conditionally Normal The American Statistician. 45: 125-126. DOI: 10.2307/2684374 |
0.502 |
|
| 1991 |
King G, Gelman A. Systemic Consequences of Incumbency Advantage in U.S. House Elections American Journal of Political Science. 35: 110. DOI: 10.2307/2111440 |
0.318 |
|
| 1990 |
Gelman A, King G. Estimating Incumbency Advantage without Bias American Journal of Political Science. 34: 1142. DOI: 10.2307/2111475 |
0.387 |
|
| 1990 |
Gelman A, King G. Estimating the electoral consequences of legislative redistricting Journal of the American Statistical Association. 85: 274-282. DOI: 10.1080/01621459.1990.10476199 |
0.374 |
|
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