The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.
Rejecting or Accepting Parameter Values in Bayesian Estimation
Open accessAbstract
This article explains a decision rule that uses Bayesian posterior distributions as the basis for accepting or rejecting null values of parameters. This decision rule focuses on the range of plausible values indicated by the highest density interval of the posterior distribution and the relation between this range and a region of practical equivalence (ROPE) around the null value. The article also discusses considerations for setting the limits of a ROPE and emphasizes that analogous considerations apply to setting the decision thresholds for p values and Bayes factors.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
The cited source says what the claim attributes to it.
In the citing paper
“There is no uniquely correct ROPE; however, by convention, the ROPE range is often set at half the size of Cohen’s definition of small effect size (i.e. 0.2 [306];) resulting in ROPE values of ±0.1 and ±0.05 for standardized mean differences (e.g. Cohen’s d = group 1 mean – group 2 mean/pooled standard deviation) and standardized regression coefficients (i.e. sβ = coefficient from a regression on”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Statistical Power Analysis for the Behavioral Sciences
Muller, K. E., & Cohen, J. (1989) · Technometrics · doi:10.2307/1270020 · Cited by 99,603
Statistical 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
Kass, R. E., & Raftery, A. E. (1995) · Journal of the American Statistical Association · doi:10.1080/01621459.1995.10476572 · Cited by 12,558
The ASA Statement on p -Values: Context, Process, and Purpose
Wasserstein, R. L., & Lazar, N. A. (2016) · The American Statistician · doi:10.1080/00031305.2016.1154108 · Cited by 6,306 · cited 1×
“Discrete decisions should be avoided if possible, because such decisions encourage people to ignore the magnitude of the parameter value and its uncertainty (e.g., Cumming, 2014; Kruschke & Liddell, 2018b; Wasserstein & Lazar, 2016, and many references cited therein).”
BackgroundJAGS: A program for analysis of Bayesian graphical models using Gibbs sampling
Plummer, M. (2003) · Cited by 4,720
The Confrontation between General Relativity and Experiment
Will, C. M. (2014) · Living Reviews in Relativity · doi:10.12942/lrr-2014-4 · Cited by 3,996
The New Statistics: Why and How
Cumming, G. (2014) · Psychological Science · doi:10.1177/0956797613504966 · Cited by 3,200
Bayes, T. (1763) · Philosophical Transactions of the Royal Society of London · doi:10.1098/rstl.1763.0053 · Cited by 3,023
AN ESSAY TOWARDS SOLVING A PROBLEM IN THE DOCTRINE OF CHANCES
BAYES (1958) · Biometrika · doi:10.1093/biomet/45.3-4.296 · Cited by 2,939
Redefine statistical significance
Benjamin, D. J., Berger, J. O., Johannesson, M., Nosek, B. A., Wagenmakers, E.-J., Berk, R., Bollen, K. A., Brembs, B., Brown, L., Camerer, C., et al. (2017) · Nature Human Behaviour · doi:10.1038/s41562-017-0189-z · Cited by 2,772
Research works printed but not linked: 5
- Jeffreys H., 1961, Theory of probability
- Lakens D., 2017, t, 8, 355
- Lesaffre E., 2008, Bulletin of the NYU Hospital for Joint Diseases, 66, 150
- Little T. A., 2015, BioPharm International, 28, 45
- Westlake W. J., 1981, Biometrics, 37, 591
Cited by
Sorted by citations
Items 501–600 of 742
Benz, G., Ludwig, T., & Vorholzer, A. (2025) · Science Education · doi:10.1002/sce.21985 · Cited by 1
Mitchell, M. J., Felice, R., Ewen, J., Ferrie, G., Royer, E., Medina, S., Newland, S., & Trask, A. E. (2025) · Animal Conservation · doi:10.1111/acv.70023 · Cited by 1
Kaźmierczak, I., & Lacko, D. (2025) · Journal of Rational-Emotive & Cognitive-Behavior Therapy · doi:10.1007/s10942-025-00607-z · Cited by 1
“Finally, all models were reevaluated using the Region of Practical Equivalence (ROPE; Kruschke, 2018) as an equivalence testing approach to determine whether any effects could be considered practically insignificant.”
Kühlwein, F., Merk, S., Schneider, J. M., & Schmidt, K. A. (2025) · Learning and Instruction · doi:10.1016/j.learninstruc.2025.102179 · Cited by 1
No silver bullets: Why understanding software cycle time is messy, not magic
Flournoy, J., Lee, C. S., Wu, M., & Hicks, C. M. (2025) · Empirical Software Engineering · doi:10.1007/s10664-025-10735-w · Cited by 3
“…Article Notebook We find that all measured factors, both individual-difference and within-person deviations, have a non-zero association with cycle time, with 100% of the posterior distribution for these parameters sharing the same sign (see Table 2 for point estimates and uncertainty intervals).”
Zaú, P. N. S., Ferreira, C. E. L., Netto, E. B. F., Mendes, T. C., & Barneche, D. R. (2025) · Functional Ecology · doi:10.1111/1365-2435.70186 · Cited by 1
Verdú, M. M., Waltzing, B. M., Caenegem, E. E. V., Czilczer, C., Boidequin, L., Truong, C., Dahm, S. F., & Hardwick, R. M. (2026) · Behavior Research Methods · doi:10.3758/s13428-026-03002-3 · Cited by 2
Turi, A., Zloteanu, M., Solescu, D. M., Rebeleș, M., & Visu‐Petra, L. (2025) · Applied Cognitive Psychology · doi:10.1002/acp.70132 · Cited by 1
Morimoto, N., Kikuchi, H., Nishihama, Y., Sohara, E., Uchida, S., & Nakayama, S. F. (2025) · Ecotoxicology and Environmental Safety · doi:10.1016/j.ecoenv.2025.119330 · Cited by 1
Cui, A., Hu, G., Yeganeh, N. M., VanHandel, L., Hermiston, N., Werker, J. F., Boyd, L. A., & Ciocca, V. (2025) · Musicae Scientiae · doi:10.1177/10298649251385724 · Cited by 1
“Hence, we defined ROPEs as intervals of ± 0.1 in standard scores as ± half the size of a small effect (Kruschke, 2018).”
InfluentialTowards a better understanding of real-life hearing impairments via electrophysiology
Schmidt, F., Reisinger, L., Neff, P. K. A., Hannemann, R., Masquelier, T., & Weisz, N. (2025) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc58623.2025.11253977 · Cited by 1
“…statistically significant if 89% of the highest (probability) density interval (HDI) of the posterior for a given standardized β -coefficient was not overlapping with a region of practical equivalence between -0.1 and 0.1 as suggested by Kruschke [34] based on negligible effect sizes [35] .”
InfluentialPublic trust in regional policymaking and citizen demands for engagement
Fellnhofer, K., Vähämaa, E., & Angelidou, M. (2025) · npj Urban Sustainability · doi:10.1038/s42949-025-00307-8 · Cited by 1
Djamnezhad, D., Bergström, M., Delfin, C., & Hofvander, B. (2025) · PLOS mental health. · doi:10.1371/journal.pmen.0000487 · Cited by 1
“To assess differences in change over time between groups, results are presented as point estimates, which are the medians from the posteriors, along with the associated 90% highest posterior density interval (HDI), i.e., the 90% most likely values of the posterior [88].”
Measuring Executive function: Performance-based versus self-report, evidence from a community sample
Çakır, R., Karahan, M., & Alpay, E. H. (2025) · Applied Neuropsychology Adult · doi:10.1080/23279095.2025.2601965 · Cited by 1
Jäckel, P. K., Dege, D. C., & Posten, A. (2026) · Forensische Psychiatrie Psychologie Kriminologie · doi:10.1007/s11757-025-00913-3 · Cited by 1
Are individual differences in lexical and coarticulatory biases linked across speech tasks?
Zhai, W., Clayards, M. A., & Sonderegger, M. (2026) · The Journal of the Acoustical Society of America · doi:10.1121/10.0042222 · Cited by 1
Lucendo‐Noriega, A., Sääkslahti, A., Ansani, A., Henttonen, K., Carlson, E. J., Saarikallio, S. H., Toiviainen, P., & Linnavalli, T. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1729705 · Cited by 1
“Moreover, we resorted to the concept of ROPE (Region of Practical Equivalence) to assess the effect size (Kruschke, 2018; Makowski et al., 2019b); in particular, we computed how much of the 89% credible interval of the parameter distributions fell within the ROPE (for the rationale behind the 89%…”
Minor, S. (2026) · Behavior Research Methods · doi:10.3758/s13428-025-02934-6 · Cited by 1
“…of an effect that is not only statistically significant but also theoretically and/or practically relevant (cf. the notions of minimal important difference [MID] in clinical and behavioral research and region of practical equivalence in Bayesian analysis; Crosby et al., 2003; Kruschke, 2014, 2018).”
Nielsen, A. L., Spedden, M. E., Beck, M. M., Jespersen, L., Bjørndal, J. R., Christensen, M. S., Karabanov, A. N., & Lundbye‐Jensen, J. (2026) · NeuroImage · doi:10.1016/j.neuroimage.2026.121884 · Cited by 1
Gavigan, L., Harry Prapavessis, A., & Chavarria, J. (2026) · Addictive Behaviors · doi:10.1016/j.addbeh.2026.108684 · Cited by 2
No added cost: Emotion recognition in co‐occurring ADHD and ASD
Plank, I. S., Krasniqi, K., Pior, A., Nowak, J., & Falter‐Wagner, C. M. (2026) · British Journal of Clinical Psychology · doi:10.1111/bjc.70056 · Cited by 1
“For some effects, we additionally performed equivalence tests based on the region of practical equivalence (ROPE) as proposed by Kruschke (2018) allowing us to assess not only differences but also equivalence between groups.”
Tang, D., Fu, Y., Li, X., Wang, H., Parviainen, T. M., & Kärkkäinen, T. (2026) · Bilingualism Language and Cognition · doi:10.1017/s1366728926101394 · Cited by 1
Rojahn, J., & Zechser, F. (2026) · Review of Accounting and Finance · doi:10.1108/raf-12-2024-0560 · Cited by 1
Carvalho, H. M., Miguel, C. G., & Gonçalves, C. E. (2026) · Frontiers in Sports and Active Living · doi:10.3389/fspor.2026.1872966 · Cited by 1
“[28].”
Madrid, J., Ulrich, B., Selig, M., Jolles, B. M., Favre, J., & Benninger, D. H. (2026) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2026.1878271 · Cited by 1
“The ROPE was set based on a small effect size (0.2 standard deviations from the data of all parameters) to define the threshold of practical equivalence (Kruschke, 2018).”
InfluentialBayesian Inference: Parameter Estimation for Inference in Small Samples
Baig, S. A. (2021) · Nicotine & Tobacco Research · doi:10.1093/ntr/ntab221 · Cited by 1
“To facilitate inference, the HDI is compared to the ROPE so that the null hypothesis is rejected when the ROPE does not overlap with the HDI and accepted when the ROPE lies entirely inside the HDI; if the HDI and ROPE overlap at all, then the null hypothesis is neither accepted nor rejected.(7) An advantage of this ap…”
Radloff, P., & Schweppe, J. (2022) · Auditory Perception & Cognition · doi:10.1080/25742442.2022.2123193 · Cited by 1
Comparing example generation with classification in the learning of new mathematics concepts
Kinnear, G. (2022) · Research in Mathematics Education · doi:10.1080/14794802.2022.2152086 · Cited by 1
“The HDI is the range of values around the median value which contain 95% of the mass of the posterior distribution, and has the property that no value outside the HDI is more credible than a value inside the HDI (Kruschke, 2018).”
BackgroundKelter, R. (2023) · Sankhya A · doi:10.1007/s13171-023-00321-x · Cited by 1
Rivera, A. S., Pak, K. J., Mefford, M. T., & Hechter, R. C. (2023) · Open Forum Infectious Diseases · doi:10.1093/ofid/ofad695 · Cited by 1
“ROPE tells us the percentage of the posterior draws that lie in the region of “practically no effect or difference,” which we set at ± 2 eGFR units [25].”
BackgroundAffinity Diagramming with a Robot
Law, M. V., Nwagwu, N., Kwatra, A., Lee, S.-Y., Diangelis, D. M., Yu, N., Gonzalez-Pumariega, G., Rajesh, A., & Hoffman, G. (2024) · ACM Transactions on Human-Robot Interaction · doi:10.1145/3641514 · Cited by 3
“To evaluate an effect in completion time, we compared an 89% highest density interval (HDI) for the posterior distribution of the mean difference in completion time between treatments to a region of practical equivalence (ROPE) of 0.1 standard deviations around zero [ 49 ].”
MethodInfluentialKelter, R., & Schnurr, A. (2024) · Statistics in Biosciences · doi:10.1007/s12561-024-09430-z · Cited by 1
“Also, the FBET obtains a widely used decision rule for interval hypothesis testing based on the region of practical equivalence (ROPE) [27, 28] as a special case, see [24].”
Robust Inference of Dynamic Covariance Using Wishart Processes and Sequential Monte Carlo
Huijsdens, H., Leeftink, D., Geerligs, L., & Hinne, M. (2024) · Entropy · doi:10.3390/e26080695 · Cited by 1
“Furthermore, covariance estimates that deviate less than 0.005 from zero (or c ) are regarded as zero (or c ) by using the region of practical equivalence (ROPE) principle [56].”
MethodInfluentialFast Power Curve Approximation for Posterior Analyses
Hagar, L., & Stevens, N. T. (2024) · Bayesian Analysis · doi:10.1214/24-ba1469 · Cited by 1
“Hypothesis testing methods with credible intervals have also been proposed (Gubbiotti and De Santis, 2011; Brutti et al., 2014; Kruschke, 2018).”
Pain and the perception of space in fibromyalgia
Scandola, M., Beccherle, M., Polati, E., Pietroni, G., Rossato, E., Schweiger, V., & Moro, V. (2025) · Scientific Reports · doi:10.1038/s41598-024-82711-1 · Cited by 1
“…sample size of 24 participants per group was necessary to achieve a 95% credible interval of the posterior distribution completely outside, or completely within the Region of Practical Equivalence (the “range of parameter values that are equivalent to the null value for practical purposes” 33 ).”
Motesharei, A., de Souza, K., Harder, B., & Pailhé, R. (2025) · Journal of Orthopaedic Experience & Innovation · doi:10.60118/001c.124659 · Cited by 1
Domazetoska, I., & Zhao, H. (2025) · Language Learning · doi:10.1111/lang.12710 · Cited by 2
“Following Kruschke (2018), we set the range from − 0.1 to 0.1 of a standardized parameter, which equals a negligible effect size put forward by Cohen (1988).”
InfluentialPerez, T. M., Adhia, D. B., Glue, P., Zeng, J., Dillingham, P. W., Navid, M. S., Niazi, I. K., Young, C. K., Smith, M. L., & Ridder, D. J. M. K. D. (2025) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/s13415-025-01279-z · Cited by 2
“Table 9 shows summary statistics for each primary subscale and includes the posterior of the mean standardised regression coefficient (sβ) with 95% HDI, pd of the sβ, and % in ± 0.05 ROPE of the sβ.”
InfluentialHolder, N. D., Batten, A. J., Shiner, B. R., Neylan, T. C., & Maguen, S. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.119472 · Cited by 2
Postictal resting-state connectivity changes after electroconvulsive therapy-induced seizures
Pottkämper, J. C. M., Verdijk, J. P. A. J., Stuiver, S., ten Doesschate, F., van Putten, M. J. A. M., Hofmeijer, J., van Waarde, J. A., & van Wingen, G. A. (2025) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-025-02043-7 · Cited by 1
“If 95% of the posterior beta coefficient fell within the ROPE, equivalence was inferred [30].”
Costantini, I., Montout, A. X., Moran, P., Kounali, D., Pearson, R. M., & Ludwig, C. J. H. (2025) · Computational Psychiatry · doi:10.5334/cpsy.134 · Cited by 1
“Because of the heavy tails of this distribution, half-16 Cauchy prior distributions are generally defined as “weakly informative” because it allows data to dominate if there is strong likelihood of the data in that region (Gelman, 2006).”
Schreiber, A., Davis, M. T., & Cawood, C. D. (2025) · Cognitive Behaviour Therapy · doi:10.1080/16506073.2025.2572480 · Cited by 2
“To this end, we conducted tests of noninferiority using Bayesian region of practical equivalence (ROPE) analyses (see Supplement for details; Kruschke, 2018).”
Wirtz, M. A. (2025) · Journal of Germanic Linguistics · doi:10.1017/s1470542725100135 · Cited by 1
“We also defined a region of practical equivalence (ROPE) to a range of ± 0.10, which reflects “ the range of parameter values that are equivalent to the null value for practical purposes ” (see Kruschke 2018:272).”
Influential“Bayesian New Statistics” as a New Direction for Psychophysiology
Yamagata, T., & Mizutori, S. (2025) · Japanese Journal of Physiological Psychology and Psychophysiology · doi:10.5674/jjppp.2604si · Cited by 1
Improving the Reliability and Generalizability of Scientific Research
Tiokhin, L. (2018) · Cited by 2
Organic Matter Sources, Composition, and Quality in Rivers and Experimental Streams
Kelso, J. E. (2021) · Digital Commons - USU (Utah State University) · doi:10.26076/6efd-4b55 · Cited by 1
Masharipov, R. S., Kireev, M. V., Korotkov, A. D., & Medvedev, S. V. (2020) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2020.09.159 · Cited by 1
Jones, A. L. (2021) · Evolution and Human Behavior · doi:10.1016/j.evolhumbehav.2021.09.002 · Cited by 1
Effects of Sentence Output Tasks on EFL Vocabulary Learning from a Bayesian Perspective
Bao, G. (2022) · English Language Literature & Culture · doi:10.11648/j.ellc.20220701.14 · Cited by 1
Rusman, E., Nadolski, R. J., & Ackermans, K. (2023) · Social interaction in learning and development · doi:10.1007/978-3-031-29411-2_10 · Cited by 1
Liao, J., Midya, V., & Berg, A. S. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1903.03153 · Cited by 1
“Alternatively, Krushke and others (Kruschke, 2018, 2011, 2013, 2014; Carlin and Louis, 2008; Edwards and Berry, 2010; Freedman et al., 1984; Hobbs and Carlin, 2007) have championed a procedure called ROPE (region of practical equivalence), in which the interval null is treated as a region of…”
BackgroundMethodProtracted development of visuo-proprioceptive integration for uni-and bimanual motor coordinationPreprint
Martel, M., Ossandón, J., Habets, B., & Heed, T. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/601435 · Cited by 1
Political Economy of Cross-Border Income Shifting: A Protection-Racket ApproachPreprint
Ananyev, M. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3384459 · Cited by 1
Kelter, R. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1906.07524 · Cited by 1
“7 The proposal for a shift towards estimation under uncertainty The two major drawbacks of the proposal of Kruschke [21] and Kruschke & Liddell [22] are that the ROPE still facilitates hypothesis testing, enforcing a binary decision of rejection or acceptance, while it is also unclear what to do when the 95%-HPD lies…”
MethodElsey, J. W. B. (2021) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/kt4pz · Cited by 3
Suzuki, A. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2108.05100 · Cited by 1
Practical Relevance: A Formal DefinitionPreprint
Schwaferts, P., & Augustin, T. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2110.09837 · Cited by 1
“…(see e.g. Lakens, 2017; Lakens et al., 2018), regions of practical equivalence (ROPE) around the null value in Bayesian decision rules (see e.g. Kruschke, 2015, 2018), or interval-valued null hypotheses in the context of Bayes factors (see e.g. Morey and Rouder, 2011; Hoijtink et al., 2019;…”
BackgroundMethodInfluentialFaces do not attract more attention than non-social distractors in the Stroop taskPreprint
Henschel, A., Bargel, H., & Cross, E. S. (2020) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/pbfny · Cited by 1
“Here, a range of plausible values are considered (indicated by the highest density interval (HDI) of the posterior distribution) and how they relate to a region of practical equivalence (ROPE) around null (Kruschke, 2018).”
BackgroundMethodInfluentialPuri, R., George, R. J. S., & Hinder, M. R. (2022) · doi:10.31234/osf.io/rgsmf · Cited by 1
Replication of “null results” – Absence of evidence or evidence of absence?Preprint
Pawel, S., Heyard, R., Micheloud, C., & Held, L. (2023) · eLife · doi:10.7554/elife.92311.1 · Cited by 1
“…advanced meth-ods for quantifying evidence for absent effects which could potentially improve on the more basic approaches considered here ( Lindley, 1998 ; Johnson and Rossell, 2010 ; Morey and Rouder, 2011 ; Kruschke, 2018 ; Stahel, 2021 ; Micheloud and Held, 2023 ; Izbicki et al., 2023 ).”
Backgroundpcvr: Plant Phenotyping and Bayesian Statistics
Sumner, J., & Berry, J. C. (2024) · doi:10.32614/cran.package.pcvr · Cited by 1
Pasanta, D., Powell, H., Hafeez, N., Lythgoe, D. J., & Puts, N. A. J. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.11.28.625809 · Cited by 1
Williams, Z. J., Dwyer, P. S. R., Poulsen, R. E., Barrett, D. J., Keçeli-Kaysılı, B., Cascio, C. J., & Woynaroski, T. G. (2025) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/4qryg_v1 · Cited by 1
Pasanta, D., Lythgoe, D. J., & Puts, N. A. J. (2025) · medRxiv · doi:10.1101/2025.05.08.25327171 · Cited by 1
“This test can be used to assess whether an observed effect is meaningfully different from zero, or another specific value within the context-defined "null-hypothesis" or range indicating a negligible effect size, also known as Range of Practical Equivalence (ROPE) 27,28 .”
InfluentialPrediction tendency, eye movements, and attention in a unified framework of neural speech trackingPreprint
Schubert, J., Gehmacher, Q., Schmidt, F., Hartmann, T., & Weisz, N. (2025) · eLife · doi:10.7554/elife.101262.2 · Cited by 1
powerbrmsINLA: Bayesian Power Analysis Using 'brms' and 'INLA'
Myers, T. (2025) · doi:10.32614/cran.package.powerbrmsinla · Cited by 1
Predicting emotional valence in autism: a preregistered study in the Bayesian Brain framework
Plank, I. S., Pior, A., Yurova, A., Nowak, J., Shi, Z., & Falter-Wagner, C. M. (2026) · Molecular Autism · doi:10.1186/s13229-026-00730-3 · Cited by 2
“Additionally, we used the region of practical equivalence (ROPE), capturing outcome values between ± 0.1 for standardised parameters, and the highest density interval (HDI) to assess evidence for equivalence [49].”
InfluentialCan Bayes Factors "Prove" the Null Hypothesis?Preprint
Smithson, M. J. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1907.05583
“If we must make a decision for or against the null, we could a priori select a small range around the null, as in Kruschke's recommendation12 (Kruschke, 2011, 2018) a "region of practical equivalence" (ROPE).”
BackgroundNot All Claims are Created Equal: Choosing the Right Approach to Assess Your Hypotheses.Preprint
Azer, E. S., Khashabi, D., Sabharwal, A., & Roth, D. (2019) · arXiv (Cornell University)
Semantic and Prosodic Threat Processing in Trait AnxietyPreprint
Busch‐Moreno, S., Tuomainen, J., & Vinson, D. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.01.24.918375
Kelter, R., & Stern, J. M. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.03334
“• The results obtained do not depend on the researcher’s intentions (Kruschke, 2018).”
BackgroundMethodInfluentialWhitham, W. (2022) · Digital Archive @ GSU · doi:10.57709/18629955
Spencer, C. (2020) · Journal of International Crisis and Risk Communication Research
Busch‐Moreno, S. (2020) · UCL Discovery (University College London)
Semantic and Prosodic Threat Processing in Trait AnxietyPreprint
Busch‐Moreno, S., Vinson, D., & Tuomainen, J. (2020) · OSF Preprints (OSF Preprints) · doi:10.17605/osf.io/z8pgf
Bayesian two-interval testPreprint
Meyer, N., & Sauleau, E. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2107.01271
“However, the ROPE neglects the important aspect of the formulation of an alternative hypothesis.”
BackgroundMethodInfluentialLacko, D., & Prošek, . (2021) · TESTFÓRUM · doi:10.5817/tf2021-14-13648
“Aposteriorní distribuci lze charakterizovat např. prostřednictvím HDI (High Density Interval; Kruschke, 2018).”
InfluentialHendrickse, J., & Yeaton, W. H. (2021) · Evaluation Review · doi:10.1177/0193841x211064420
“More specifically, we multiplied the SD of the RCT pretest for the control group at the individual level by .30 or .10 to create a lenient threshold (Steiner andWong, 2016) or a stringent threshold (Cook et al., 2020; Kruschke, 2018), respectively.”
BackgroundMethodPractical Implications of Equating Equivalence Tests: Reply to Campbell and Gustafson (2022)Preprint
Linde, M., Tendeiro, J. N., Wagenmakers, E., & van Ravenzwaaij, D. (2022) · doi:10.31234/osf.io/xk43y
Expectations for Rhythmic Sounds Increase Bottom-Up Visual AttentionPreprint
Motz, B. A., Kruschke, J. K., Hetrick, W. P., James, T. W., & Puce, A. (2022) · doi:10.31234/osf.io/b2uaj
Self-citationBret, A., Beffara, B., Mierop, A., & Mermillod, M. (2017) · doi:10.31234/osf.io/3mfa8
Unconscious Visual Working Memory: a critical review and Bayesian meta-analysisPreprint
Gambarota, F., Tsuchiya, N., Pastore, M., Polito, N. D., & Sessa, P. (2021) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/gt67h · Cited by 1
Unaware attitude formation in the surveillance task? Revisiting the findings of Moran et al. (2021)Preprint
Kurdi, B., Hussey, I., Stahl, C., Hughes, S., Unkelbach, C., Ferguson, M. J., & Corneille, O. (2020) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/thmcn
Sterner, P., Friemelt, B., Goretzko, D., Kraus, E. B., Bühner, M., & Pargent, F. (2022) · doi:10.31234/osf.io/rsqvt
Mental rotation and schizotypal personality traits: A Bayesian approach
García‐Pérez, Á., González‐Rodríguez, A., Godoy‐Giménez, M., Sayans‐Jiménez, P., Cañadas, F., & Estévez, Á. F. (2022) · Scandinavian Journal of Psychology · doi:10.1111/sjop.12874 · Cited by 2
Blackburn, A. M., Han, H., Jeftić, A., Stöckli, S., Gelpí, R., Acosta-Ortiz, A., Travaglino, G. A., Alvarado, R., Lacko, D., Milfont, T. L., et al. (2023) · doi:10.31234/osf.io/75jq2
Intra- and inter-brain synchrony oscillations underlying social adjustmentPreprint
Vicente, U., Ara, A., & Marco‐Pallarés, J. (2023) · Research Square · doi:10.21203/rs.3.rs-2728662/v1
Bayesian Generalized Linear Mixed Effects Models for Deception Detection AnalysesPreprint
Zloteanu, M., & Vuorre, M. (2023) · doi:10.31234/osf.io/fdh5b
The genetic architecture of differentiating behavioural and emotional problems in early lifePreprint
Askelund, A. D., Hegemann, L., Allegrini, A. G., Corfield, E. C., Ask, H., Davies, N. M., Andreassen, O. A., Havdahl, A., & Hannigan, L. J. (2023) · Research Square · doi:10.21203/rs.3.rs-3223835/v1
Delfin, C. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1253452 · Cited by 7
“Finally, future work may also want to consider other approaches to defining an acceptable range, such as using the region of practical equivalence (Kruschke, 2018).”
BackgroundYeaton, W. H., & Velasquez, G. (2022) · Journal of Methods and Measurement in the Social Sciences · doi:10.2458/jmmss.5793
Sawada, T. (2023) · The Quantitative Methods for Psychology · doi:10.20982/tqmp.19.3.p281
“Many other assumptions are also never strictly satisfied and the effects of their violation are quantitative (Blanca et T he Q uantitative M ethods for P sychology 281 2 al., 2018; Fagerland, 2012; Kasuya, 2001; van den Bergh et al., 2023).”
BackgroundInfluentialViljoen, D., Labuschagné, F. J. W. J., & Kuehnert, I. (2023) · Advanced Industrial and Engineering Polymer Research · doi:10.1016/j.aiepr.2023.11.001
The HDI+ROPE decision rule is logically incoherent but we can fix itPreprint
Etz, A. J., la Peña, A. F. C. D., Baroja, J. L., Medriano, K., & Vandekerckhove, J. (2023) · doi:10.31234/osf.io/5p2qt
“While we are strong proponents of the Bayesian statistical paradigm (Etz & Vandekerckhove, 2018; Vandekerckhove, Rouder, & Kruschke, 2018) in which HRDR is based, we will argue here that HRDR is flawed and should be avoided, on grounds similar to the above objections to NHST. Specifically, HRDR can…”
Peng, D.-C., Cowie, S., Moreau, D., & Addis, D. R. (2024) · Cognition · doi:10.1016/j.cognition.2024.105718
Metadata
- Authors
- Kruschke, J. K.
- Affiliations
- Indiana University Bloomington (US)
- Corresponding author
- Kruschke, John K.
- ORCID
- Kruschke, John K.
- Venue
- Advances in Methods and Practices in Psychological Science
- Publisher
- SAGE Publications
- Published
- 2018-05-08
- Volume
- 1
- Issue
- 2
- Pages
- 270-280
- ISSN
- 2515-2459 (ISSN-L)
- 2515-2467
- OpenAlex
- W2801776818
- Cited by
- 734
- References
- 51
- Citations by year
- 2026: 99 · 2025: 128 · 2024: 128 · 2023: 98 · 2022: 85 · 2021: 93 · 2020: 67 · 2019: 25 · 2018: 10
- FWCI
- 41.08
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Advances in Methods and Practices in Psychological Science (publishedVersion)
- IUScholarWorks Open (Indiana University) (submittedVersion)
- OSF Preprints (OSF Preprints) (submittedVersion)
- Funders
- U.S. Food and Drug Administration
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Distribution Estimation and Applications
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- Bayesian hypothesis testing, null hypothesis rejection, highest density interval, region of practical equivalence, posterior distribution, decision threshold, p-values, Bayes factor, parameter values
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
