{"id":18507666,"url":"https://github.com/mihaiconstantin/sample-size-workshop","last_synced_at":"2026-01-30T14:34:01.952Z","repository":{"id":171924978,"uuid":"635756346","full_name":"mihaiconstantin/sample-size-workshop","owner":"mihaiconstantin","description":"Workshop on Sample Size Planning for Intensive Longitudinal Studies","archived":false,"fork":false,"pushed_at":"2023-06-08T09:44:39.000Z","size":41813,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-08-07T05:49:21.530Z","etag":null,"topics":["data-science","power-analysis","sample-size","statistics","time-series","workshop"],"latest_commit_sha":null,"homepage":"https://samplesize.help","language":"TeX","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/mihaiconstantin.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-05-03T11:48:38.000Z","updated_at":"2023-06-06T21:02:23.000Z","dependencies_parsed_at":null,"dependency_job_id":"f802462b-0160-41ea-82ce-afa4645f1063","html_url":"https://github.com/mihaiconstantin/sample-size-workshop","commit_stats":null,"previous_names":["mihaiconstantin/sample-size-workshop"],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/mihaiconstantin/sample-size-workshop","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mihaiconstantin%2Fsample-size-workshop","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mihaiconstantin%2Fsample-size-workshop/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mihaiconstantin%2Fsample-size-workshop/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mihaiconstantin%2Fsample-size-workshop/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mihaiconstantin","download_url":"https://codeload.github.com/mihaiconstantin/sample-size-workshop/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mihaiconstantin%2Fsample-size-workshop/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28914312,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-30T12:13:43.263Z","status":"ssl_error","status_checked_at":"2026-01-30T12:13:22.389Z","response_time":66,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data-science","power-analysis","sample-size","statistics","time-series","workshop"],"created_at":"2024-11-06T15:11:16.920Z","updated_at":"2026-01-30T14:34:01.923Z","avatar_url":"https://github.com/mihaiconstantin.png","language":"TeX","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003c!-- Repository title. --\u003e\n\u003ch1 align=\"center\"\u003e\n    Workshop on Sample Size Planning for\n    \u003cbr\u003e\n    Intensive Longitudinal Studies\n\u003c/h1\u003e\n\n\u003c!-- Authors. --\u003e\n\u003cp align=\"center\"\u003e\n    \u003ca href=\"presenters/ginette-lafit.md\"\u003eGinette Lafit\u003c/a\u003e,\n    \u003ca href=\"presenters/jordan-revol.md\"\u003eJordan Revol\u003c/a\u003e,\n    \u003ca href=\"presenters/mihai-constantin.md\"\u003eMihai A. Constantin\u003c/a\u003e, \u0026\n    \u003ca href=\"presenters/eva-ceulemans.md\"\u003eEva Ceulemans\u003c/a\u003e\n\u003c/p\u003e\n\n\u003c!-- Badges. --\u003e\n\u003cp align=\"center\"\u003e\n    \u003ca href=\"https://doi.org/10.5281/zenodo.8015940\"\u003e\u003cimg src=\"https://zenodo.org/badge/DOI/10.5281/zenodo.8015940.svg\" alt=\"DOI\"\u003e\u003c/a\u003e\n\u003c/p\u003e\n\n## 📝 Description\n\nIn recent years the popularity of procedures to collect intensive longitudinal\ndata such as the Experience Sampling Method has increased immensely. The data\ncollected using such designs allow researchers to study the dynamics of\npsychological processes, and how these dynamics differ across individuals. A\nfundamental question when designing a study is how to determine the sample size,\nwhich is closely related to the replicability and generalizability of empirical\nfindings. Even though multiple statistical guidelines are available for sample\nsize planning, it still remains a demanding enterprise in complex designs. The\ngoal of this workshop is to address this crucial question by presenting\nmethodological advances for sample size planning for intensive longitudinal\ndesigns. First, we provide an overview of methods for sample size planning with\nspecial emphasis on a priori power analysis. Second, we focus on how to conduct\npower analysis in the $N = 1$ case when the goal is to model within-person\nprocesses using $\\text{VAR}(1)$ models. Subsequently, we consider the extension\nto multilevel data in which multiple individuals are measured over time. We\nintroduce an approach for conducting power analysis for multilevel models that\nexplicitly accounts for the temporal dependencies that characterize the data\ncollected in IL studies. In addition, we showcase how to perform power analysis\nfor these models using a user-friendly and open-source application. Finally, we\nconsider an alternative criterion for conducting sample size planning that\ntargets the predictive accuracy of a model for unseen data. Focusing on\n$\\text{VAR}(1)$ models in an $N = 1$ context, we introduce a novel approach,\ncalled predictive accuracy analysis, to assess how many measurement occasions\nare required in order to optimize predictive accuracy.\n\n---\n\n\u003ch3 align=\"center\"\u003e\n    Check out the materials and more at \u003cbr\u003e\n    \u003ca href=\"https://samplesize.help\"\u003esamplesize.help\u003c/a\u003e\n\u003c/h3\u003e\n\n---\n\n## ✍️ Citation\n\n- Lafit, G., Revol, J., Constantin M. A., \u0026 Ceulemans, E. (2023). *Workshop on\n  Sample Size Planning for Intensive Longitudinal Studies*.\n  [https://doi.org/10.5281/zenodo.8015940](https://doi.org/10.5281/zenodo.8015940)\n\n## ⚖️ License\n\n- \u003cp class=\"license-cc\" xmlns:cc=\"https://creativecommons.org/ns#\" xmlns:dct=\"https://purl.org/dc/terms/\"\u003e\u003ca property=\"dct:title\" rel=\"cc:attributionURL\" href=\"https://github.com/mihaiconstantin/sample-size-workshop\"\u003eThe scripts, slides, and other materials\u003c/a\u003e by \u003ca rel=\"cc:attributionURL dct:creator\" property=\"cc:attributionName\" href=\"https://github.com/mihaiconstantin/sample-size-workshop#citation\"\u003eGinette Lafit, Jordan Revol, Mihai A. Constantin, and Eva Ceulemans\u003c/a\u003e are licensed under \u003ca href=\"https://creativecommons.org/licenses/by/4.0/?ref=chooser-v1\" target=\"_blank\" rel=\"license noopener noreferrer\" style=\"display:inline-block;\"\u003eCC BY 4.0 \u003cimg style=\"height:22px!important\" src=\"https://mirrors.creativecommons.org/presskit/icons/cc.svg?ref=chooser-v1\"\u003e \u003cimg style=\"height:22px!important\" src=\"https://mirrors.creativecommons.org/presskit/icons/by.svg?ref=chooser-v1\"\u003e\u003c/a\u003e.\u003c/p\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmihaiconstantin%2Fsample-size-workshop","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmihaiconstantin%2Fsample-size-workshop","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmihaiconstantin%2Fsample-size-workshop/lists"}