Section author: Laiton Hedley

Overview

When you bring your data into jamovi, it is not always ready for analysis. You may need to recode responses, reverse score items, exclude outliers, or compute new scores across multiple columns.

jamovi provides three primary tools for working with data: Computed Variables, Transformed Variables, and Filters. You can find these tools in the Data tab along the top of the jamovi window:

The jamovi Data ribbon showing the Compute, Transform, and Filter buttons.

Checking Your Data

All data in jamovi starts as Data Variables — the raw columns you bring in or enter directly. Before you start transforming, check that each variable has the correct Measure type and Data type, and that missing values are handled correctly.

The Three Tools

Computed Variables

Create new columns derived from existing ones using a formula — for example, summing item scores or computing a z-score. These are best suited for one-off calculations.

Transformed Variables

Apply reusable transformations to one or more source columns — for example, reverse scoring a set of Likert items. You can apply the same transform to many columns at once.

Filters

Restrict which rows are included in your analyses without deleting any data. For example, you can exclude participants who failed an attention check.

Quick Reference

Not sure which one to reach for? Use this table:

If you want to…

Use

Calculate a new value for each row (e.g., sum score, z-score)

Computed Variable

Apply the same rule across many columns (e.g., reverse scoring 10 items)

Transformed Variable

Recode values into categories (e.g., age groups, grade labels)

Transformed Variable

Include only certain rows in your analyses

Filter

Exclude outliers without deleting them

Filter

Reference and How-To