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What is Cramer’s V?
Cramer’s V is used to understand the strength of the relationship between two variables. To use it, your variables of interest should be categorical with two or more unique values per category. See more below.
Cramer’s V is also known as Cramer’s Phi.
Assumptions for Cramer’s V
Every statistical method has assumptions. Assumptions mean that your data must satisfy certain properties in order for statistical method results to be accurate.
The assumptions for Cramer’s V include:
- Categorical variables
Let’s dive into what that means.
For this test, your two variables must be categorical. A categorical variable is a variable that describes a category that doesn’t relate naturally to a number. Examples of categorical variables are eye color, city of residence, type of dog, etc.
When to use the Cramer’s V?
You should use the Cramer’s V in the following scenario:
- You want to know the relationship between two variables
- Your variables of interest are categorical
- You have two or more unique values per category
Let’s clarify these to help you know when to use Cramer’s V
You are looking for a statistical test to look at how two variables are related. Other types of analyses include testing for a difference between two variables or predicting one variable using another variable (prediction).
A categorical variable is a variable that describes a category that doesn’t relate naturally to a number. Examples of categorical variables are eye color, city of residence, type of dog, etc..
Two or More Distinct Values
To perform Cramer’s V, there must be two or more unique values in each of your categorical variables. If there are only two unique values, then using Cramer’s V is the same as using the Phi Coefficient.
Cramer’s V Example
Variable 1: Political Party
Variable 2: Favorite Musical Genre
In this example, we are interested in investigating the relationship between political party and favorite musical genre. To begin, we collect these data from a group of people.
Because both of these variables are categorical with two or more possible values per variable, we know that Cramer’s V is a suitable test.
The analysis will result in a Cramer’s V value and a p-value. Cramer’s V ranges from 0 to 1, where 0 indicates no relationship and 1 indicates perfect association
The p-value represents the chance of seeing our results if there was no actual relationship between our variables. A p-value less than or equal to 0.05 means that our result is statistically significant and we can trust that the difference is not due to chance alone.
Frequently Asked Questions
Q: How do I calculate Cramer’s V in SPSS or R?
A: StatsTest is focused on helping you pick the right statistical method every time. There are many resources available to help you figure out how to run this method with your data:
SPSS article: https://www.spss-tutorials.com/cramers-v-what-and-why/
SPSS video: https://www.youtube.com/watch?v=kxM3a42IkE8
R article: https://jasminedaly.com/tech-short-papers/Example_of_CramersV_Calculation.html
R video: https://www.youtube.com/watch?v=cMysfAyDkKA
If you still can’t figure something out, feel free to reach out.