--- title: A Guide on Estimating Long-Term Effects in A/B Tests description: Short-term experiment results often differ from the long-term due to factors like heterogeneous treatment effects or user learning. Methods for identifying... canonical: https://daily.dev/posts/a-guide-on-estimating-long-term-effects-in-a-b-tests-cwzve155c twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: A Guide on Estimating Long-Term Effects in A/B Tests | daily.dev og:description: Short-term experiment results often differ from the long-term due to factors like heterogeneous treatment effects or user learning. Methods for identifying... og:url: https://daily.dev/posts/a-guide-on-estimating-long-term-effects-in-a-b-tests-cwzve155c og:image: https://api.daily.dev/og/posts/CWzVe155c.png og:image:alt: A Guide on Estimating Long-Term Effects in A/B Tests og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # A Guide on Estimating Long-Term Effects in A/B Tests **[Towards Data Science](https://daily.dev/sources/tds)** · 8 min read · 1 upvotes · 0 comments ## Summary Short-term experiment results often differ from the long-term due to factors like heterogeneous treatment effects or user learning. Methods for identifying trends in long-term effects include visualization, ladder experiment assignment, difference-in-difference, random vs constant treatment assignment, and user 'unlearning'. The long-term effects can be predicted using auto-surrogate models that forecast the long-term outcome of the experiment. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: --- Tags: [#data-science](https://daily.dev/tags/data-science), [#statistics](https://daily.dev/tags/statistics), [#ab-testing](https://daily.dev/tags/ab-testing) [View this post on daily.dev](https://daily.dev/posts/a-guide-on-estimating-long-term-effects-in-a-b-tests-cwzve155c) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"A Guide on Estimating Long-Term Effects in A/B Tests","url":"https://daily.dev/posts/a-guide-on-estimating-long-term-effects-in-a-b-tests-cwzve155c","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/a-guide-on-estimating-long-term-effects-in-a-b-tests-cwzve155c"},"datePublished":"2024-02-24T14:26:49.028Z","dateModified":"2024-05-09T09:06:08.895Z","description":"Short-term experiment results often differ from the long-term due to factors like heterogeneous treatment effects or user learning. Methods for identifying...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/63604e9f1a8705a02611cf75122b3649?_a=AQAEufR","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/63604e9f1a8705a02611cf75122b3649?_a=AQAEufR","isAccessibleForFree":true,"articleSection":"Towards Data Science","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Towards Data Science","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/tds","url":"https://daily.dev/sources/tds"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/a-guide-on-estimating-long-term-effects-in-a-b-tests-cwzve155c","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":1},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"data-science,statistics,ab-testing","timeRequired":"PT8M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Towards Data Science","item":"https://daily.dev/sources/tds"},{"@type":"ListItem","position":3,"name":"A Guide on Estimating Long-Term Effects in A/B Tests"}]} ```