The DOI matches its Crossref record; 44 of the 44 references it cites were found in a registry or an index.
The earth is round (p < .05).
Abstract
After 4 decades of severe criticism, the ritual of null hypothesis significance testing (mechanical dichotomous decisions around a sacred .05 criterion) still persists. This article reviews the problems with this practice, including near universal misinterpretation of p as the probability that H₀ is false, the misinterpretation that its complement is the probability of successful replication, and the mistaken assumption that if one rejects H₀ one thereby affirms the theory that led to the test. Exploratory data analysis and the use of graphic methods, a steady improvement in and a movement toward standardization in measurement, an emphasis on estimating effect sizes using confidence intervals, and the informed use of available statistical methods are suggested. For generalization, psychologists must finally rely, as has been done in all the older sciences, on replication. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“As in any statistical application, accepting the null hypothesis (in this case, a null hypothesis of no interaction) should be understood as being distinct from a failure to reject it (Cohen, 1994).”
From Enrichment Effects on Adult Cognitive Development: Can the Functional Capacity of Older Adults Be Preserved and Enhanced? (2008) · cites this paper as Cohen, 1994
In the citing paper
“Therefore, NHST only tells us about the probability of obtaining data which are equally or more discrepant than those obtained in the event that H0 is true (Cohen, 1994; Nickerson, 2000; Balluerka et al., 2009; Kline, 2013).”
From Misconceptions of the p-value among Chilean and Italian Academic Psychologists (2016) · cites this paper as Cohen, 1994
In the citing paper
“The most common misconceptions about p-value are “inverse probability fallacy,” “replication fallacy,” “effect size fallacy,” and “clinical or practical significance fallacy” (Carver, 1978; Cohen, 1994; Kirk, 1996; Nickerson, 2000; Kline, 2013).”
From Misconceptions of the p-value among Chilean and Italian Academic Psychologists (2016) · cites this paper as Cohen, 1994
In the citing paper
“This is might be because of two reasons: the programmer could have found a problem while coding, who at first will try to solve it by reading the code, switching out from the IDE, navigating the call stack and debugging, before going to ask another teammate, according to LaToza et al. [35]; this set of actions end up with an interruption and reduce the observed activity within the IDE.”
From Work fragmentation in developer interaction data (2017) · cites this paper as [35]
In the citing paper
“These categories of events agree with our previous hypothesis that positive interruptions are related to information seeking [9,35], while negative interruptions are related to actual task switches where context needs to be rebuilt afterwards.”
From Work fragmentation in developer interaction data (2017) · cites this paper as [35]
In the citing paper
“Our results and theoretical foundations are based on observational studies performed on information workers' development environments [5,6,35,10].”
From Work fragmentation in developer interaction data (2017) · cites this paper as [35]
Citations
Cites
Statistical power analysis for the behavioral sciences
Cohen, J. (1990) · Computers Environment and Urban Systems · doi:10.1016/0198-9715(90)90050-4 · Cited by 65,417
Self-citationStatistical Power Analysis for the Behavioral Sciences (2nd ed.).
Lachenbruch, P. A., & Cohen, J. (1989) · Journal of the American Statistical Association · doi:10.2307/2290095 · Cited by 37,421
Self-citationDavid, F. N., & Tukey, J. W. (1977) · Biometrics · doi:10.2307/2529486 · Cited by 12,707
Statistical Methods for Research Workers
Fisher, R. A. (1945) · American Journal of Clinical Pathology · doi:10.1093/ajcp/15.11.552b · Cited by 10,883
The file drawer problem and tolerance for null results.
Rosenthal, R. (1979) · Psychological Bulletin · doi:10.1037/0033-2909.86.3.638 · Cited by 9,068
The Logic of Scientific Discovery
Bhaskar, R. (2013) · Routledge eBooks · doi:10.4324/9780203090732-9 · Cited by 7,765
The visual display of quantitative information
(1985) · General Pharmacology The Vascular System · doi:10.1016/0306-3623(85)90230-7 · Cited by 5,090
Belief in the law of small numbers.
Tversky, A., & Kahneman, D. (1971) · Psychological Bulletin · doi:10.1037/h0031322 · Cited by 3,246
Kemp, C. D., & Tufte, E. R. (1992) · Biometrics · doi:10.2307/2532323 · Cited by 2,728
Meehl, P. E. (1978) · Journal of Consulting and Clinical Psychology · doi:10.1037/0022-006x.46.4.806 · Cited by 2,061
Cited by
Sorted by citations
Items 101–200 of 1,029
Thompson, B. (2002) · Educational Researcher · doi:10.3102/0013189x031003025 · Cited by 546
How to Estimate and Interpret Various Effect Sizes.
Vacha‐Haase, T., & Thompson, B. (2004) · Journal of Counseling Psychology · doi:10.1037/0022-0167.51.4.473 · Cited by 556
Default Bayes Factors for Model Selection in Regression
Rouder, J. N., & Morey, R. D. (2012) · Multivariate Behavioral Research · doi:10.1080/00273171.2012.734737 · Cited by 477
Does ChatGPT enhance student learning? A systematic review and meta-analysis of experimental studies
Deng, R., Jiang, M., Yu, X., Lu, Y., & Liu, S. (2025) · Computers & Education · doi:10.1016/j.compedu.2024.105224 · Cited by 531
Contrasts and Correlations in Effect-Size Estimation
Rosnow, R. L., Rosenthal, R., & Rubin, D. B. (2000) · Psychological Science · doi:10.1111/1467-9280.00287 · Cited by 513
Jodoin, M. G., & Gierl, M. J. (2001) · Applied Measurement in Education · doi:10.1207/s15324818ame1404_2 · Cited by 519
Silverman, W. K., Kurtines, W. M., Ginsburg, G. S., Weems, C. F., Lumpkin, P. W., & Carmichael, D. H. (1999) · Journal of Consulting and Clinical Psychology · doi:10.1037//0022-006x.67.6.995 · Cited by 512
MCDANIEL, M. (2005) · Intelligence · doi:10.1016/j.intell.2004.11.005 · Cited by 527
Handbook of multimethod measurement in psychology.
Eid, M., & Diener, E. (2006) · American Psychological Association eBooks · doi:10.1037/11383-000 · Cited by 497
Three ways to make replication mainstream
Gantman, A. P., Gomila, R., Martinez, J. E., Matias, J., Paluck, E., Starck, J. G., Wu, S., & Yaffe, N. (2017) · Behavioral and Brain Sciences · doi:10.1017/s0140525x17001972 · Cited by 302
Keith, N., & Fresé, M. (2005) · Journal of Applied Psychology · doi:10.1037/0021-9010.90.4.677 · Cited by 511
Presidential Address: The Scientific Outlook in Financial Economics
Harvey, C. R. (2017) · The Journal of Finance · doi:10.1111/jofi.12530 · Cited by 466
Middel, B., & van Sonderen, E. (2002) · International Journal of Integrated Care · doi:10.5334/ijic.65 · Cited by 463
Kruschke, J. K., Aguinis, H., & Joo, H. (2012) · Organizational Research Methods · doi:10.1177/1094428112457829 · Cited by 478
Cumming, G. (2008) · Perspectives on Psychological Science · doi:10.1111/j.1745-6924.2008.00079.x · Cited by 451
Cliff´s Delta Calculator: A non-parametric effect size program for two groups of observations
Macbeth, G., Razumiejczyk, E., & Ledesma, R. D. (2010) · Universitas Psychologica · doi:10.11144/javeriana.upsy10-2.cdcp · Cited by 442
A randomized controlled trial of Hanen's ‘More Than Words’ in toddlers with early autism symptoms
Carter, A. S., Messinger, D. S., Stone, W. L., Celimli, S., Nahmias, A. S., & Yoder, P. (2011) · Journal of Child Psychology and Psychiatry · doi:10.1111/j.1469-7610.2011.02395.x · Cited by 446
An Alternative to Null-Hypothesis Significance Tests
Killeen, P. R. (2005) · Psychological Science · doi:10.1111/j.0956-7976.2005.01538.x · Cited by 443
Design and Analysis of Cluster Randomization Trials in Health Research
Davis, W. W. (2001) · Journal of the American Statistical Association · doi:10.1198/jasa.2001.s433 · Cited by 1,735
Robust misinterpretation of confidence intervals
Hoekstra, R., Morey, R. D., Rouder, J. N., & Wagenmakers, E.-J. (2014) · Psychonomic Bulletin & Review · doi:10.3758/s13423-013-0572-3 · Cited by 425
Principles and procedures of exploratory data analysis.
Behrens, J. T. (1997) · Psychological Methods · doi:10.1037/1082-989x.2.2.131 · Cited by 465
Stepwise Regression and Stepwise Discriminant Analysis Need Not Apply here: A Guidelines Editorial
Thompson, B. (1995) · Educational and Psychological Measurement · doi:10.1177/0013164495055004001 · Cited by 434
Effect Size, Practical Importance, and Social Policy for Children
McCartney, K., & Rosenthal, R. (2000) · Child Development · doi:10.1111/1467-8624.00131 · Cited by 429
Prins, N., & Kingdom, F. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.01250 · Cited by 449
Amrhein, V., Trafimow, D., & Greenland, S. (2019) · The American Statistician · doi:10.1080/00031305.2018.1543137 · Cited by 432
Wicherts, J. M., Bakker, M., & Molenaar, D. (2011) · PLoS ONE · doi:10.1371/journal.pone.0026828 · Cited by 424
From Resource Base to Dynamic Capabilities: an Investigation of New Firms
McKelvie, A., & Davidsson, P. (2009) · British Journal of Management · doi:10.1111/j.1467-8551.2008.00613.x · Cited by 453
Abandon Statistical SignificancePreprint
McShane, B. B., Gal, D., Gelman, A., Robert, C. P., & Tackett, J. L. (2019) · HAL · Cited by 449
McShane, B. B., Böckenholt, U., & Hansen, K. T. (2016) · Perspectives on Psychological Science · doi:10.1177/1745691616662243 · Cited by 398
Rouder, J. N., & Lu, J. (2005) · Psychonomic Bulletin & Review · doi:10.3758/bf03196750 · Cited by 413
Effect sizes for experimenting psychologists.
Rosnow, R. L., & Rosenthal, R. (2003) · Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale · doi:10.1037/h0087427 · Cited by 416
Assessing the impact of climate variation on survival in vertebrate populations
Grosbois, V., Giménez, O., Gaillard, J., Pradel, R., Barbraud, C., Clobert, J., Møller, A. P., & Weimerskirch, H. (2008) · Biological reviews/Biological reviews of the Cambridge Philosophical Society · doi:10.1111/j.1469-185x.2008.00047.x · Cited by 432
Computation of measures of effect size for neuroscience data sets
Hentschke, H., & Stüttgen, M. C. (2011) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2011.07902.x · Cited by 421
A Practical Primer To Power Analysis for Simple Experimental Designs
Perugini, M., Gallucci, M., & Costantini, G. (2018) · International Review of Social Psychology · doi:10.5334/irsp.181 · Cited by 482
Anderson, S. F., Kelley, K., & Maxwell, S. E. (2017) · Psychological Science · doi:10.1177/0956797617723724 · Cited by 406
How clients make therapy work: The process of active self-healing.
Bohart, A. C., & Tallman, K. (1999) · American Psychological Association eBooks · doi:10.1037/10323-000 · Cited by 411
Nuts and Bolts of Conducting Feasibility Studies
Tickle‐Degnen, L. (2013) · American Journal of Occupational Therapy · doi:10.5014/ajot.2013.006270 · Cited by 457
The epistemology of mathematical and statistical modeling: A quiet methodological revolution.
Rodgers, J. L. (2010) · American Psychologist · doi:10.1037/a0018326 · Cited by 402
Thompson, B. (2002) · Journal of Counseling & Development · doi:10.1002/j.1556-6678.2002.tb00167.x · Cited by 398
The influence of chronically and temporarily accessible information on life satisfaction judgments.
Schimmack, U., & Oishi, S. (2005) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.89.3.395 · Cited by 393
Swedberg, R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108762519.002 · Cited by 471
Tryon, W. (2001) · Psychological methods · doi:10.1037/1082-989x.6.4.371 · Cited by 423
Researchers Misunderstand Confidence Intervals and Standard Error Bars.
Belia, S., Fidler, F., Williams, J., & Cumming, G. (2005) · Psychological Methods · doi:10.1037/1082-989x.10.4.389 · Cited by 390
Bayesian Estimation and Inference
Zyphur, M. J., & Oswald, F. L. (2013) · Journal of Management · doi:10.1177/0149206313501200 · Cited by 415
Effect sizes, confidence intervals, and confidence intervals for effect sizes
Thompson, B. (2007) · Psychology in the Schools · doi:10.1002/pits.20234 · Cited by 392
Gauch Jr, H. G. (2002) · doi:10.1017/cbo9780511815034 · Cited by 385
Enhancing the Interpretation of Significant Findings: The Role of Mixed Methods Research
Onwuegbuzie, A. J., & Leech, N. L. (2015) · The Qualitative Report · doi:10.46743/2160-3715/2004.1913 · Cited by 398
Evolution of Reporting P Values in the Biomedical Literature, 1990-2015
Chavalarias, D., Wallach, J. D., Li, A. H. T., & Ioannidis, J. P. A. (2016) · JAMA · doi:10.1001/jama.2016.1952 · Cited by 370
Vieten, C., & Astin, J. (2008) · Archives of Women's Mental Health · doi:10.1007/s00737-008-0214-3 · Cited by 369
The Effectiveness of Second Language Strategy Instruction: A Meta‐analysis
Plonsky, L. (2011) · Language Learning · doi:10.1111/j.1467-9922.2011.00663.x · Cited by 417
Grover, S. C. (2004) · Childhood · doi:10.1177/0907568204040186 · Cited by 381
Gendreau, P., Goggin, C., & Law, M. A. (1997) · Criminal Justice and Behavior · doi:10.1177/0093854897024004002 · Cited by 376
Krueger, J. I., & Funder, D. C. (2004) · Behavioral and Brain Sciences · doi:10.1017/s0140525x04000081 · Cited by 374
Integrating explanation and prediction in computational social science
Hofman, J. M., Watts, D. J., Athey, S., Garip, F., Griffiths, T. L., Kleinberg, J., Margetts, H., Mullainathan, S., Salganik, M. J., Vazire, S., et al. (2021) · Nature · doi:10.1038/s41586-021-03659-0 · Cited by 371
A systematic review of effect size in software engineering experiments
Kampenes, V. B., Dybå, T., Hannay, J. E., & Sjøberg, D. I. K. (2007) · Information and Software Technology · doi:10.1016/j.infsof.2007.02.015 · Cited by 370
Bäckström, M., Björklund, F., & LARSSON, M. R. (2009) · Journal of Research in Personality · doi:10.1016/j.jrp.2008.12.013 · Cited by 366
Evidence for publication bias in video game violence effects literature: A meta-analytic review
Ferguson, C. J. (2007) · Aggression and Violent Behavior · doi:10.1016/j.avb.2007.01.001 · Cited by 398
Psychology Will Be a Much Better Science When We Change the Way We Analyze Data
Loftus, G. R. (1996) · Current Directions in Psychological Science · doi:10.1111/1467-8721.ep11512376 · Cited by 362
Toward an Empirical Definition of Pediatric PTSD: The Phenomenology of PTSD Symptoms in Youth
Carrión, V. G., Weems, C. F., Ray, R. D., & Reiss, A. L. (2002) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1097/00004583-200202000-00010 · Cited by 362
Information theory and hypothesis testing: a call for pluralism
Stephens, P., Buskirk, S., Hayward, G., & del Rio, C. (2005) · Journal of Applied Ecology · doi:10.1111/j.1365-2664.2005.01002.x · Cited by 317
Halsey, L. G. (2019) · Biology Letters · doi:10.1098/rsbl.2019.0174 · Cited by 382
The (mis)reporting of statistical results in psychology journals
Bakker, M., & Wicherts, J. M. (2011) · Behavior Research Methods · doi:10.3758/s13428-011-0089-5 · Cited by 356
The scientific study of dreams: Neural networks, cognitive development, and content analysis.
Domhoff, G. W. (2003) · doi:10.1037/10463-000 · Cited by 355
Cumming, G., & Finch, S. (2001) · Educational and Psychological Measurement · doi:10.1177/0013164401614002 · Cited by 528
The relation between statistical power and inference in fMRI
Cremers, H. R., Wager, T. D., & Yarkoni, T. (2017) · PLoS ONE · doi:10.1371/journal.pone.0184923 · Cited by 356
Bayesian analysis of factorial designs.
Rouder, J. N., Morey, R. D., Verhagen, J., Swagman, A. R., & Wagenmakers, E. (2016) · Psychological Methods · doi:10.1037/met0000057 · Cited by 353
Plonsky (2013) · doi:10.1017/s0272263113000399 · Cited by 347
An Introduction to Bayesian Hypothesis Testing for Management Research
Andraszewicz, S., Scheibehenne, B., Rieskamp, J., Grasman, R. P. P. P., Verhagen, J., & Wagenmakers, E. (2014) · Journal of Management · doi:10.1177/0149206314560412 · Cited by 370
Violent Video Games and Aggression
Ferguson, C. J., Rueda, S. M., Cruz, A. M., Ferguson, D. E., Fritz, S., & Smith, S. M. (2008) · Criminal Justice and Behavior · doi:10.1177/0093854807311719 · Cited by 344
Streiner, D. L. (2015) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.115.113548 · Cited by 344
Sun, S.-Y., Pan, W., & Wang, L. (2010) · Journal of Educational Psychology · doi:10.1037/a0019507 · Cited by 329
AERA Editorial Policies regarding Statistical Significance Testing: Three Suggested Reforms
Thompson, B. (1996) · Educational Researcher · doi:10.2307/1176337 · Cited by 339
Krygier, J. R., Heathers, J. A. J., Shahrestani, S., Abbott, M., Gross, J. J., & Kemp, A. H. (2013) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2013.06.017 · Cited by 327
The Insignificance of Null Hypothesis Significance Testing
Gill, J. (1999) · Political Research Quarterly · doi:10.1177/106591299905200309 · Cited by 330
Estriégana, R., Medina, J., & Barchino, R. (2019) · Computers & Education · doi:10.1016/j.compedu.2019.02.010 · Cited by 357
Fair Statistical Communication in HCI
Dragicevic, P. (2016) · Human-computer interaction series · doi:10.1007/978-3-319-26633-6_13 · Cited by 365
THE INCORPORATION OF EFFECT SIZE IN INFORMATION TECHNOLOGY, LEARNING, AND PERFORMANCE RESEARCH
Kotrlik, J. W., & Williams, H. A. (2003) · Cited by 334
Zakzanis, K. K. (2001) · Archives of Clinical Neuropsychology · doi:10.1093/arclin/16.7.653 · Cited by 346
Weigold, A., Weigold, I. K., & Russell, E. J. (2013) · Psychological Methods · doi:10.1037/a0031607 · Cited by 379
Sprouse, J., Schütze, C. T., & Almeida, D. (2013) · Lingua · doi:10.1016/j.lingua.2013.07.002 · Cited by 344
The Public Health Risks of Media Violence: A Meta-Analytic Review
Ferguson, C. J., & Kilburn, J. C. (2009) · The Journal of Pediatrics · doi:10.1016/j.jpeds.2008.11.033 · Cited by 330
Sex Bias in Infectious Disease Epidemiology: Patterns and Processes
Guerra-Silveira, F., & Abad‐Franch, F. (2013) · PLoS ONE · doi:10.1371/journal.pone.0062390 · Cited by 334
A tutorial on support vector machine-based methods for classification problems in chemometrics
Luts, J., Ojeda, F., de Plas, R. V., Moor, B. D., Huffel, S. V., & Suykens, J. A. K. (2010) · Analytica Chimica Acta · doi:10.1016/j.aca.2010.03.030 · Cited by 336
Psychonarratology foundations for the empirical study of literary response
Bortolussi, M., & Dixon, P. A. (2003) · Cited by 328
A Systematic Review on the Practice of Evaluating Visualization
Tobias Isenberg, A., Isenberg, P., Jian, C., Sedlmair, M., & Möller, T. B. (2013) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2013.126 · Cited by 324
Reporting effect sizes in original psychological research: A discussion and tutorial.
Pek, J. C. X., & Flora, D. B. (2017) · Psychological Methods · doi:10.1037/met0000126 · Cited by 356
The Use of Structural Equation Modeling in Counseling Psychology Research
Martens, M. P. (2005) · The Counseling Psychologist · doi:10.1177/0011000004272260 · Cited by 343
Five-factor model of personality and employee absence.
Judge, T. A., Martocchio, J. J., & Thoresen, C. J. (1997) · Journal of Applied Psychology · doi:10.1037/0021-9010.82.5.745 · Cited by 317
Downing, M. G., Sanfilippo, A., Maruff, P. T., Weih, L. M., & Phillips, K. (2005) · Brain and Cognition · doi:10.1016/j.bandc.2005.05.001 · Cited by 314
Reporting and Interpreting Effect Size in Quantitative Agricultural Education Research
Kotrlik, J. W., Williams, H. A., & Jabor, M. K. (2011) · Journal of Agricultural Education · doi:10.5032/jae.2011.01132 · Cited by 314
The Congruence Myth: An Analysis of the Efficacy of the Person–Environment Fit Model
Tinsley, H. E. A. (2000) · Journal of Vocational Behavior · doi:10.1006/jvbe.1999.1727 · Cited by 314
Greenland, S. (2019) · The American Statistician · doi:10.1080/00031305.2018.1529625 · Cited by 313
The use of likelihood-based confidence intervals in genetic models
Neale, M. C., & Miller, M. B. (1997) · Behavior Genetics · doi:10.1023/a:1025681223921 · Cited by 310
Kelley, K., & Maxwell, S. E. (2003) · Psychological Methods · doi:10.1037/1082-989x.8.3.305 · Cited by 310
The earth is flat ( p > 0.05): significance thresholds and the crisis of unreplicable research
Amrhein, V., Korner‐Nievergelt, F., & Roth, T. (2017) · PeerJ · doi:10.7717/peerj.3544 · Cited by 331
Lahey, B. B., Schwab‐Stone, M., Goodman, S. H., Waldman, I. D., CANINO, G. J., Rathouz, P. J., Miller, T. L., Dennis, K., Bird, H., & Jensen, P. S. (2000) · Journal of Abnormal Psychology · doi:10.1037/0021-843x.109.3.488 · Cited by 307
Applying evolutionary models to the laboratory study of social learning
McElreath, R. L., Lubell, M. N., Richerson, P. J., Waring, T. M., Baum, W. M., Edsten, E., Efferson, C. M., & Paciotti, B. M. (2005) · Evolution and Human Behavior · doi:10.1016/j.evolhumbehav.2005.04.003 · Cited by 296
An Ounce of Prevention Is Worth a Pound of Cure: Improving Research Quality Before Data Collection
Aguinis, H., & Vandenberg, R. J. (2014) · Annual Review of Organizational Psychology and Organizational Behavior · doi:10.1146/annurev-orgpsych-031413-091231 · Cited by 304
ISO 9000/1994, ISO 9001/2000 and TQM: The performance debate revisited
Costa, M. M., Choi, T. Y., García, J. A. M., & Lorente, Á. R. M. (2009) · Journal of Operations Management · doi:10.1016/j.jom.2009.04.002 · Cited by 317
Final Collapse of the Neyman-Pearson Decision Theoretic Framework and Rise of the neoFisherian
Hurlbert, S. H., & Lombardi, C. M. (2009) · Annales Zoologici Fennici · doi:10.5735/086.046.0501 · Cited by 305
Metadata
- Authors
- Cohen, J.
- Affiliations
- New York University (US)
- Corresponding author
- Cohen, Jacob
- Venue
- American Psychologist
- Published
- 1994-12
- Volume
- 49
- Issue
- 12
- Pages
- 997-1003
- ISSN
- 0003-066X (ISSN-L)
- 1935-990X
- OpenAlex
- W2030360178
- Cited by
- 4,003
- References
- 43
- Citations by year
- 2026: 94 · 2025: 122 · 2024: 87 · 2023: 116 · 2022: 128 · 2021: 161 · 2020: 255 · 2019: 178 · 2018: 184 · 2017: 177 · 2016: 187 · 2015: 182 · 2014: 183 · 2013: 167 · 2012: 172
- FWCI
- 87.17
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Psychologist (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Keywords
- null hypothesis significance testing, misinterpretation of p-values, replication, effect size estimation, confidence intervals, exploratory data analysis, measurement standardization, psychology research practice
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
