📅 2023-10-17 — Session: Structured RMarkdown and PanelMatch Analysis Session
🕒 20:30–21:05
🏷️ Labels: Rmarkdown, Panelmatch, Modular Design, Data Analysis
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal: The session aimed to explore and enhance understanding of RMarkdown file structures, causal analysis using PanelMatch in R, and modular code organization for data projects.
Key Activities:
- Reflected on the structure of .Rmd files, detailing metadata, R code chunks, and LaTeX file generation.
- Executed causal analysis using the PanelMatch package in R, focusing on estimating average treatment effects with covariate balance.
- Planned modular code structures for large projects, emphasizing separation of code by functionality.
- Developed a modular RMarkdown file structure to improve maintainability and collaboration.
- Revised the table of contents structure for analysis reports, detailing sections and subsections for clarity.
- Introduced R Markdown and RStudio, explaining code chunk formatting and interactive editing benefits.
- Outlined code commenting conventions in R for enhanced readability.
Achievements:
- Gained insights into the structured breakdown of RMarkdown files and data flows.
- Successfully applied PanelMatch for causal analysis in R.
- Proposed a modular design framework for both RMarkdown and large project code structures.
Pending Tasks:
- Further exploration of modular design in RMarkdown for specific data analysis workflows.
- Implementation of revised table of contents in ongoing analysis projects.