Revision history [back]

One approach to aggregate data across various factor levels without altering the original levels is to use data transformation techniques such as summarization, averaging, or grouping.

For example, suppose we have a dataset with two factors, age and gender, and a response variable, income. If we want to examine the average income of each age group and gender without altering the original levels of the factors, we can use the following steps:

1. Group the data by age and gender using a group-by function.
2. Calculate the mean of income for each age and gender group.
3. Save the results as a new dataset.

This way, we can still preserve the original levels of the age and gender factors, but we also have a summarized view of the income data by age and gender. We can use this new dataset to perform further analysis or visualization.