Key points at a glance
- Define exposure and outcome.
- Justify plausible third variables.
- Adjust design and interpretation.
Define a confounder carefully
A possible confounder relates to both the exposure and outcome and can offer an alternative explanation for their association. Not every extra measured variable qualifies. First state the exact relationship you want to examine.
Sketch an alternative explanation
Example: Students who use the library often receive higher grades. Prior knowledge or available study time might affect both library use and grades. Check what you measured and whether its timing supports the proposed explanation.
Plan around plausible confounding
Seek comparable groups, collect defensible third variables and justify eligibility rules. With observational data, stratification or a planned model can help, but cannot erase unmeasured differences. Do not add a control merely because your software allows it.
Use cautious result language
State which potential confounders were accounted for, how they were measured and which might remain. Describe cross-sectional results as associations rather than effects. An adjusted coefficient alone is not proof of causation.
Final submission context
Formal details can feel like a separate writing task, but they matter just as much for a printed submission. Anything missing, misplaced or inconsistently formatted in the document will also appear in the bound copy.
Use this guide together with your cover page, table of contents, page numbers, source notes and appendices. Prepare the final PDF for printing and binding only after the complete file has been checked.
Practical check before PDF export
- Do headings, chapter structure and page numbers match?
- Are sources, figures and tables included completely?
- Are required elements such as declarations, appendices or the cover page included where required?
- Did you open and check the final PDF after exporting it?
Checklist
- Defined relationship.
- Justified third variables.
- Checked measurement.
- Limited causal language.
Common mistakes
- Calling every covariate a confounder.
- Assuming all bias has been removed.
- Equating regression with causation.
Prepare the finished thesis for submission
Once the content and university requirements are checked, review your PDF and the available printing and binding options.
Review printing optionsRelated content
Explore related guidance on thesis structure, sources, formatting and final submission.
Frequently asked questions
What is a confounder?
A variable related to exposure and outcome that may distort their association.
Does adjustment solve it?
It can help if variables are chosen and measured well; residual bias remains possible.
Must I use regression?
No, the question and design determine the method.