15 Survival Analysis

Learning Objectives

By the end of this chapter, you will be able to:

Define censoring and explain why it breaks a standard linear model
Distinguish true from functional longevity
Contrast a binary stayability model with a true time-to-event analysis
Fit a proportional hazards model containing a genetic effect
Interpret survival EBVs and relate them to economic merit

Assumes Ch 6, Ch 14.

Chapter in progress

This chapter has not been written yet. The objectives above are the contract it will be written against — they are taken from CHAPTERS.md, which is the outline for the whole book.

Purpose. Time-to-event data and censoring.

---
title: "Survival Analysis"
---

::: {.callout-note icon=false}
## Learning Objectives

By the end of this chapter, you will be able to:

1. **Define** censoring and explain why it breaks a standard linear model
2. **Distinguish** true from functional longevity
3. **Contrast** a binary stayability model with a true time-to-event analysis
4. **Fit** a proportional hazards model containing a genetic effect
5. **Interpret** survival EBVs and relate them to economic merit
:::

*Assumes Ch 6, Ch 14.*

::: {.callout-warning}
## Chapter in progress

This chapter has not been written yet. The objectives above are the contract it will be written
against — they are taken from `CHAPTERS.md`, which is the outline for the whole book.

**Purpose.** Time-to-event data and censoring.
:::