---
title: "Risks of Bias in Research"
source: The Turing Way
source_url: https://github.com/the-turing-way/the-turing-way
licence: CC-BY-4.0
domain: data-and-analysis
subdomain: turing-way
date_added: 2026-04-25
---

(pd-risks-of-bias)=
# Risks of Bias in Research


(pd-risks-of-bias-prerequisites)=
## Prerequisites


| Prerequisite          | Importance | Notes                                                                               |
| -----------------|----------|------|
| {ref}`er-datahazards` | Helpful | Data Hazard labels can be used to highlight specific ethical risks to shareholders.  |

(pd-risks-of-bias-summary)=
## Summary
[*Risks of bias*](https://www.nhmrc.gov.au/guidelinesforguidelines/develop/assessing-risk-bias#) are opportunities for the results of research to become distorted by limitations within the study design, conduct, and analysis.
This can cause the findings and interpretation of research to be misleading or incorrect. 
Many risks can be mitigated, though this requires researchers to be aware both of the risks and the mitigation techniques. 
This chapter introduces methods for the {ref}`assessment of risks of bias <pd-risks-of-bias-identifying-risks-of-bias>`, {ref}`identification of confounders <pd-risks-of-bias-confounding-variables>`, and some {ref}`methods to improve validation <pd-risks-of-bias-validation-generalisability>`. 

In this chapter, the word *bias* predominantly refers to statistical distortion rather than to {ref}`the unfair treatment of societal groups (discrimination) <pd-risks-of-bias-discrimination-bias>`, which is an important topic in its own right.


(pd-risks-of-bias-motivation)=
## Motivation and Background

Researchers are trusted by a wide array of stakeholders. 
Governmental and advisory bodies may look to research to influence policies, effected parties to influence their personal lives, and other researchers to influence future research.
However, despite the best intentions, it can be easy to produce misleading research, leading to potential harms and the loss of trust. 

Many risks can be mitigated with careful planning of data collection and analysis, leading to more accurate research outputs. 
Where risks are inevitable, these can be made clear to stakeholders to reduce the risk of inaccuracies causing harm. 


This chapter aims to help researchers to identify and mitigate risks of bias in order to conduct research as accurately and ethically as possible, making for trustworthy, high-impact studies that can have a positive real-world impact.
