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Myalgic Encephalomyelitis / Chronic Fatigue Syndrome (ME / CFS) Post Treatment Lyme Disease Syndrome (PTLDS), Fibromyalgia Leading Research. Delivering Hope.Open Medicine Foundation® Canada
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🧬Science Wednesdays: What is Stratification?

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What is Stratification?

From the Desk of Dr. Danielle Meadows
Vice President of Research Programs & Operations

The image features Danielle Meadows with shoulder-length brown hair, wearing a dark blazer and a green top.

To round out my first year of Science Wednesdays, I wanted to talk a bit about a concept that helps address the heterogeneity of ME/CFS—stratification. This is such an important concept in complex research it actually spans both of the middle stages of the research process: “Recruitment, Data Collection” and “Data Analysis”.

The image is a flowchart with four stages of the research process. “Recruitment, Data Collection” and “Data Analysis” are highlighted, indicating emphasis.

The heterogeneity of ME/CFS likely impacts so much of what we understand (and don’t) about the disease. Stratification is probably the best way to address that while still being inclusive of the broader population with ME/CFS in a study.

The Heart of the Matter

  • Stratification is a fancy way of saying that participants in a research study are divided into subgroups, or stratified, based on specific characteristics (like sex or age). It helps researchers determine how those characteristics influence the results.
  • Stratification is important for research on ME/CFS because it gives study teams a more detailed understanding of what’s going on in the disease, which can lead to personalized medicine.
  • As an example, OMF’s Melbourne ME/CFS Collaboration is stratifying their analysis by sex for the Serial Paediatrics Omics Tracking in ME (SPOT-ME) project.

Stratification is an important concept in research, especially for chronic complex diseases like ME/CFS, Long COVID, and similar conditions. 

What Is Stratification?

Stratification is, broadly speaking, the act of dividing a population into subgroups. In the context of research, stratification is a concept that spans across two stages of the research process:

  • Recruitment, Data Collection: Stratification typically comes into play during participant randomization (i.e., when participants are assigned to a study group). It is a way of guaranteeing that previously defined subgroups—generally based on characteristics related to the research question—are represented in each study group. For example, you might stratify randomization by sex, which will mean that each of your study groups will have the same ratio of females to males. 
  • Data Analysis: Stratification then carries through into the data analysis stage as you try to understand the impact of the subgroups on the data. In many cases, the factors defining the subgroups will be confounders—something that complicates the relationship between the variables being studied—so the stratification helps control and understand the impact those confounders have on the results.


OMF’s Melbourne ME/CFS Collaboration, for example, will utilize stratification in the analysis of their study called Serial Paediatrics Omics Tracking in Myalgic Encephalomyelitis (SPOT-ME). Their goal with stratification in this case is to understand how biological sex impacts the relationship between markers in the blood and symptoms in the participants. For more information about this project and the stratified analysis, you can read the SPOT-ME protocol paper in BMJ Open.

Why Is Stratification Important?

Stratification can be particularly important for research on heterogeneous diseases like ME/CFS and Long COVID. Through stratified analysis, study teams can get a more detailed or precise understanding of the disease and how it differs based on the characteristics that are used for the stratification. Down the road, that information can then enable better patient outcomes through practices like personalized medicine.

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