Vibe-Skills performing-causal-analysis

Fits causal models, estimates impacts, and plots results using CausalPy. Use when performing analysis with DiD, ITS, SC, or RD.

install

source · Clone the upstream repo

git clone https://github.com/foryourhealth111-pixel/Vibe-Skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/foryourhealth111-pixel/Vibe-Skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/bundled/skills/performing-causal-analysis" ~/.claude/skills/foryourhealth111-pixel-vibe-skills-performing-causal-analysis && rm -rf "$T"

manifest: bundled/skills/performing-causal-analysis/SKILL.md

Performing Causal Analysis

Executes causal analysis using CausalPy experiment classes.

Workflow

Load Data: Ensure data is in a Pandas DataFrame.
Initialize Experiment: Use the appropriate class (see References).
Fit & Model: Models are fitted automatically upon initialization if arguments are provided.
Analyze Results: Use
```
summary()
```
,
```
print_coefficients()
```
, and
```
plot()
```
.

Core Methods

```
experiment.summary()
```
: Prints model summary and main results.
```
experiment.plot()
```
: Visualizes observed vs. counterfactual.
```
experiment.print_coefficients()
```
: Shows model coefficients.

References

Detailed usage for specific methods: