4. Cleaning and Preparing Data in jamovi

Before we describe, visualize, or analyze data, we need to make sure the data are ready to use. Real datasets are rarely perfect. Variables might be set up incorrectly, response options might be stored as text, missing values might need attention, or scale items might need to be combined into a total or average score.

This chapter focuses on the practical work of preparing data in . You will learn how to check your data, fix common setup problems, transform and recode variables, reverse-score items, and create scale scores. These steps may feel small, but they matter. If the data are not prepared correctly, everything that comes after this point can be affected.

By the end of this chapter, you should be able to:

Cleaning data does not mean changing the data to get the results you want. It means preparing the data so the values are accurate, meaningful, and ready for analysis.

In this chapter, you will learn how to check whether variables are set up correctly, handle missing values, identify possible data-entry errors, reverse-score items, recode or transform variables, and create scale scores. These steps matter because every descriptive statistic, graph, and inferential test depends on the quality of the variables you are analyzing.

NoteFor Dana’s Students

In my courses, you will usually submit your .omv file or screenshots showing parts of your work. That is not just busywork. It helps me see your process, not only your final answer. Save your file early, save it often, and use meaningful variable names so that your work is easier to check later.

Which jamovi Tool Do I Need?

What you need to do Tool or feature in jamovi Example
Change how jamovi understands a variable Setup Change a variable from continuous to ordinal
Mark a value as missing Setup Tell jamovi that 99 means missing
Create a new score from existing variables Compute Create a total score or average scale score
Change values based on rules Transform Convert text responses into numeric values
Reverse-score an item Transform or Compute Change 1 → 5, 2 → 4, 3 → 3, 4 → 2, 5 → 1
Combine or simplify categories Transform/recode Combine several gender responses into fewer categories
Temporarily analyze only some rows Filter Analyze only participants in one group

You do not need to memorize this table. Use it as a decision guide when you know what you want to accomplish but are not sure where to start.