---
title: >-
  The impact of parametric assumptions on the bias-variance tradeoff for causal
  analysis of time-to-event outcomes
description: >-
  Explore this publication on real-world evidence: The impact of parametric
  assumptions on the bias-variance tradeoff for causal analysis of
  time-to-event…
date: '2022-01-01'
author: Andrew G. Allmon
category: Publications
tags:
  - ICPE
  - Approval & Commercialization
  - 'Yes'
  - Oral Presentation
  - Methods/Pharmacoepi
  - R&D
canonical_url: >-
  https://www.headwaterscience.com/resources/publications/icpe/the-impact-of-parametric-assumptions-on-the-bias-variance/
source: Headwater Science
license: © 2026 Headwater Science. All rights reserved.
slug: the-impact-of-parametric-assumptions-on-the-bias-variance
id: 55S0bg1FmbG2qHNw6IqgJ
contentType: article
---

## Challenge

The choice of parametric assumptions in survival analysis models for time-to-event outcomes involves a fundamental bias-variance trade-off, but the practical implications of this trade-off for causal analyses of real-world treatment effects had not been systematically examined.

## Solution

Target RWE researchers presented a systematic examination of how parametric model specification choices affect the bias-variance trade-off in causal time-to-event analyses, characterizing the conditions under which flexible versus restrictive models are preferable.

## Impact

Providing guidance on parametric model selection for time-to-event causal analyses enables Target RWE and pharma partners to make principled analytic choices that minimize bias while maintaining appropriate variance.

## Use Cases / Links

Parametric model selection guidance for bias-variance trade-off in causal time-to-event analyses, Survival analysis methodology for regulatory-grade RWE treatment effectiveness programs