{"id":19844563,"url":"https://github.com/repsychling/mb1","last_synced_at":"2026-06-11T17:31:34.135Z","repository":{"id":110422126,"uuid":"239480070","full_name":"RePsychLing/mb1","owner":"RePsychLing","description":"Analysis of data from the ManyBabies study","archived":false,"fork":false,"pushed_at":"2020-02-28T14:37:10.000Z","size":2176,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-02-28T22:50:28.773Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","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/RePsychLing.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":"2020-02-10T10:03:43.000Z","updated_at":"2020-02-22T11:57:17.000Z","dependencies_parsed_at":"2023-03-13T13:54:20.065Z","dependency_job_id":null,"html_url":"https://github.com/RePsychLing/mb1","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/RePsychLing/mb1","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RePsychLing%2Fmb1","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RePsychLing%2Fmb1/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RePsychLing%2Fmb1/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RePsychLing%2Fmb1/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/RePsychLing","download_url":"https://codeload.github.com/RePsychLing/mb1/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RePsychLing%2Fmb1/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34211061,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-11T02:00:06.485Z","response_time":57,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":[],"created_at":"2024-11-12T13:04:40.287Z","updated_at":"2026-06-11T17:31:34.117Z","avatar_url":"https://github.com/RePsychLing.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ManyBabies\n\nRe-analysis of data from the [`ManyBabies1: Infant-directed Speech Preference`](https://github.com/manybabies/mb1-analysis-public) project. \n\n\n* For more information about the ManyBabies project, see http://manybabies.stanford.edu/  \n* The data and main analysis can be found at https://github.com/manybabies/mb1-analysis-public, stimuli, protocol, and further documentation is at https://osf.io/re95x/  \n  * This is the paper (which we ask to cite if you do anything with this dataset) The ManyBabies Consortium. (2019). \"Quantifying sources of variability in infancy research using the infant-directed speech preference.\" In press at *Advances in Methods and Practices in Psychological Science (AMPPS)*. [Preprint](https://psyarxiv.com/s98ab/)\n\nThe repository contains:  \n\n* `MB1_analysis.jmd` - The main script, which  \n\n  1. Reads in ManyBabies 1 data  \n  2. Shapes it as needed  \n  3. Reproduces the main analysis from the paper at https://github.com/manybabies/mb1-analysis-public  \n  4. Fits the preregistered maximal model  \n  5. Simplifies the random effects by inspecting the output of rePCA and the variance components  \n  6. Shows what can go wrong with multi-lab data (subid vs subid_unique)  \n  7. Re-processes more messy data to apply different cleaning criteria to deal with censoring (which you can adjust)  \n  8. Re-runs the analysis  \n  \n* `MB1_analysis.ipynb` - The corresponding Jupyter notebook that you can run in your browser, but which differs from the converted version of the .jmd (split code blocks to see all output, converted R code cell)  \n* `MB1_minimal_lmer.R` - The R code needed to reproduce the main analysis of the paper, extracted from https://github.com/manybabies/mb1-analysis-public/blob/master/paper/mb1-paper.Rmd  \n* `intendend_complex_LMM.txt` - Output for the preregistered model (which still takes some time to fit)  \n* `Project.toml` and `Manifest.toml` - See https://repsychling.github.io/pkg.html  \n  \nFor instructions how to run code in .jmd and .ipynb files, see https://repsychling.github.io/intro.html\n\n\n\n## Acknowledgements\nThis work was supported by the Center for Interdisciplinary Research, Bielefeld (ZiF) Cooperation Group \"Statistical models for psychological and linguistic data\".\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frepsychling%2Fmb1","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frepsychling%2Fmb1","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frepsychling%2Fmb1/lists"}