Analyze categorical health data and visualize relationships using Multiple Correspondence Analysis.
Upload or enter your categorical data to perform MCA. Explore associations, reduce dimensions, and interpret results for research or clinical insights.
Click an example to load sample data into the calculator.
Simple example with gender and smoking status.
Categorical Data Table:
patient,gender,smoker
1,Male,Yes
2,Female,No
3,Male,No
4,Female,Yes
Delimiter: ,
Includes age group as a supplementary variable.
Categorical Data Table:
patient,gender,smoker,age_group
1,Male,Yes,Adult
2,Female,No,Senior
3,Male,No,Adult
4,Female,Yes,Senior
Delimiter: ,
Supplementary Variables: age_group
Example with gender, region, and diagnosis.
Categorical Data Table:
id,gender,region,diagnosis
1,Male,North,Diabetes
2,Female,South,Hypertension
3,Male,East,Diabetes
4,Female,West,Healthy
Delimiter: ,
Simulated clinical trial with treatment and outcome.
Categorical Data Table:
subject,treatment,outcome,center
1,DrugA,Improved,Site1
2,DrugB,NoChange,Site2
3,DrugA,Improved,Site1
4,DrugB,Worsened,Site2
Delimiter: ,
Supplementary Variables: center