{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"org.agenticjournal/paper-lakens-2017-equivalence","description":"Tests whether an effect is small enough to be treated as absent.","version":"0.2.0","title":"Equivalence Testing Agent","websiteUrl":"https://doi.org/10.1177/1948550617697177","remotes":[{"type":"streamable-http","url":"https://paper-agents-418969583050.europe-west1.run.app/tost/mcp"}],"_meta":{"org.agenticjournal.registry/agent":{"longDescription":"Runs two one-sided tests (TOST) to assess whether an observed effect falls inside equivalence bounds, so that the absence of an effect can be argued for rather than inferred from a non-significant result.","availability":"hosted","capabilityKinds":["score","critique"],"skills":[{"id":"power_tost","name":"Power tost","description":"Solve for the sample size an equivalence test needs, or the power it has.","tags":[]},{"id":"tost","name":"Tost","description":"Test whether an effect is small enough to be practically equivalent to zero.","tags":[]},{"id":"versions","name":"Versions","description":"Report the R and package versions this agent runs, and the paper it implements.","tags":[]}]},"org.agenticjournal.registry/official":{"status":"active","isLatest":true},"org.agenticjournal.registry/paper":{"doi":"10.1177/1948550617697177","title":"Equivalence Tests","year":2017,"venue":"Social Psychological and Personality Science","authors":[{"family":"Lakens","given":"Daniël"}],"csl":{"DOI":"10.1177/1948550617697177","URL":"http://dx.doi.org/10.1177/1948550617697177","ISSN":["1948-5506","1948-5514"],"link":[{"URL":"https://journals.sagepub.com/doi/pdf/10.1177/1948550617697177","content-type":"application/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https://journals.sagepub.com/doi/full-xml/10.1177/1948550617697177","content-type":"application/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https://journals.sagepub.com/doi/pdf/10.1177/1948550617697177","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"page":"355-362","type":"journal-article","issue":"4","score":1,"title":"Equivalence Tests","author":[{"role":[{"role":"author","vocabulary":"crossref"}],"given":"Daniël","family":"Lakens","sequence":"first","affiliation":[{"name":"Human Technology Interaction Group, Eindhoven University of Technology, Eindhoven, the Netherlands"}]}],"issued":{"date-parts":[[2017,5]]},"member":"179","prefix":"10.1177","source":"Crossref","volume":"8","created":{"date-time":"2017-05-05T11:47:02Z","timestamp":1493984822000,"date-parts":[[2017,5,5]]},"indexed":{"version":"4.0.1","date-time":"2026-09-21T03:20:55Z","timestamp":1789960855248,"date-parts":[[2026,9,21]]},"license":[{"URL":"https://journals.sagepub.com/page/policies/text-and-data-mining-license","start":{"date-time":"2017-05-01T00:00:00Z","timestamp":1493596800000,"date-parts":[[2017,5,1]]},"delay-in-days":0,"content-version":"tdm"}],"subject":[],"abstract":"<jats:p>Scientists should be able to provide support for the absence of a meaningful effect. Currently, researchers often incorrectly conclude an effect is absent based a nonsignificant result. A widely recommended approach within a frequentist framework is to test for equivalence. In equivalence tests, such as the two one-sided tests (TOST) procedure discussed in this article, an upper and lower equivalence bound is specified based on the smallest effect size of interest. The TOST procedure can be used to statistically reject the presence of effects large enough to be considered worthwhile. This practical primer with accompanying spreadsheet and R package enables psychologists to easily perform equivalence tests (and power analyses) by setting equivalence bounds based on standardized effect sizes and provides recommendations to prespecify equivalence bounds. Extending your statistical tool kit with equivalence tests is an easy way to improve your statistical and theoretical inferences.</jats:p>","language":"en","relation":{"has-preprint":[{"id":"10.31234/osf.io/97gpc","id-type":"doi","asserted-by":"object"},{"id":"10.31234/osf.io/97gpc_v1","id-type":"doi","asserted-by":"object"}]},"resource":{"primary":{"URL":"https://journals.sagepub.com/doi/10.1177/1948550617697177"}},"subtitle":["A Practical Primer for\n                    <i>t</i>\n                    Tests, Correlations, and Meta-Analyses"],"deposited":{"date-time":"2026-04-30T22:08:48Z","timestamp":1777586928000,"date-parts":[[2026,4,30]]},"published":{"date-parts":[[2017,5]]},"publisher":"SAGE Publications","reference":[{"DOI":"10.1037/met0000051","key":"bibr1-1948550617697177","unstructured":"Anderson S. F., Maxwell S. E. (2016). There’s more than one way to conduct a replication study: Beyond statistical significance. 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