Research reproducibility and open science

Implement reproducible research practices throughout project lifecycle. Preregistration: 1. Register study protocol before data collection (OSF, ClinicalTrials.gov). 2. Include hypotheses, methods, analysis plan, sample size justification. 3. Distinguish confirmatory from exploratory analyses. Reproducible workflow: 1. Version control: Git/GitHub for code and document management. 2. Literate programming: R Markdown, Jupyter notebooks combining code and narrative. 3. Environment management: Docker containers, package version recording. 4. Automated reporting: dynamic documents that update with new data. Open data and materials: 1. Data repositories: disciplinary (e.g., ICPSR) or general (OSF, Zenodo). 2. Code sharing: GitHub with clear documentation and README files. 3. Materials sharing: survey instruments, interview guides, stimuli. Transparency reporting: 1. CONSORT for RCTs, STROBE for observational studies. 2. Report all measures, manipulations, exclusions. Publication: preprints for rapid dissemination, open access journals when possible.