# Lab 3: Confounding & Effect Measure Collapsibility

## Overview

In this lab you will explore confounding and effect measure collapsibility using the
Right Heart Catheterization (`RHC`) dataset, investigating the association between
receiving a right-heart catheterization and all-cause mortality. You will prepare the
data, produce a descriptive summary table, and fit a series of regression models to
calculate and compare crude, conditional, and marginal effect estimates (odds ratios, risk
ratios, and risk differences) — seeing how adjustment affects each measure differently.
Your TA will walk through the worked solution during the session.

This is the workflow you will reuse in **P2** on your own locked paper.

## Materials

- **Exercise instructions:** [Confounding](https://ehsanx.github.io/EpiMethods/confoundingE.html)
- **Worked solution:** [The R codes](https://ehsanx.github.io/EpiMethods/confoundingEsolution.html)

**Before you come to lab**, install the package every model chunk uses:

```r
install.packages("Publish")   # capital P; the function you call is lowercase publish()
```

Three things to know about the downloaded exercise file:

- **Uncomment the `read.csv` line** in the first chunk. The data are in the zip's `Data/`
  folder, and nothing else runs until `df` exists.
- It says the RHC data were used in "Lab Assignment #1". That was another course. The
  wrangling code is given in full, and you are not expected to have seen these data.
- Ignore its percentage grade weights. This lab is graded Complete / Incomplete (below).

## Your task

1. Follow along as the TA explains the worked solution.
2. Run the R Markdown file yourself, as a group, on your own laptop.
3. Put your **group name and the first names of everyone present** in the `author:`
   field at the top of the file.

4. Add `sessionInfo()` in a final code chunk.
5. Knit to **PDF or HTML** and submit that one file before the lab ends.

No written explanations are required. If you get stuck, ask the TA in the room — that is
what the session is for.

## Deliverable

- **One file per group:** the knitted PDF or HTML.
- **Due:** end of the lab session (Thu Oct 1).

## Grading: Complete / Incomplete

You receive **Complete** if the document knitted without errors, your group name and
members are in it, and it was submitted before the lab ended. Only members present in the
room receive credit.

---

## Where this lab fits

This lab is one step in a weekly chain: Tuesday’s lecture sets up the method, Thursday’s lab runs it on fixed teaching data, and your increment applies it to the paper your group locked at M0.

| | Document | How this lab connects |
|---|---|---|
| **This week’s lecture** | [Week 4 — Confounding and DAGs; Table 1; variable roles](https://ehsanx.github.io/SPPH604-2026W/lectures/Week4_confounding_and_table1.html) | Tuesday used the MASLD paper to decide what to adjust for — DAGs, the empirical criteria, why change-in-estimate and stepwise selection fail — and showed why an odds or hazard ratio moves on adjustment even without confounding. This lab runs the mechanics on a different dataset (RHC): crude, conditional and marginal odds ratios, risk ratios and risk differences, and standardisation. |
| **Slide deck** | [Week 4 deck](https://ehsanx.github.io/SPPH604-2026W/lectures/slides/Week4_confounding_slides.html) | The same material as slides, with speaker notes. Press `S` for notes, `F` for fullscreen. |
| **Your increment** | [P2 — Confounding diagnostic](https://ehsanx.github.io/SPPH604-2026W/practice/P2_confounding_diagnostic.html) | Produce your own Table 1 plus a written adjustment rationale — which variables you adjust for, which you deliberately do not, and why. |
| **Worked example** | [P2 example](https://ehsanx.github.io/SPPH604-2026W/examples/P2_confounding/P2_confounding_submission.html) — [its code](https://ehsanx.github.io/SPPH604-2026W/examples/P2_confounding/P2_code.html) | A completed P2: the Table 1, and the adjustment rationale written out. Read the rationale first — it is the part that carries the marks. |
| **Milestone** | [M1 — Replication and interrogation](https://ehsanx.github.io/SPPH604-2026W/milestones/M1_assignment.html) | P2 enters M1 as **Confounding, adjustment set, Table 1**. P2 is optional and ungraded with nothing to submit; M1 is where it is assessed. |