Navigate to the Data tab > select variable Age > Transform

A new variable will appear to the right of the variable you want to transform. 

Name your new variable. In this case, we will name it Over_50 

Sometimes you may also want to add a description.

You can change the source variable in the Source Variable field, but you won't usually need to do this for a simple transformation. 

Using transform > click None > Create new transform... 

Jamovi gives each transformation a name - change it. This allows you to use it again later on other variables if you wish. You can also add a description.

If you plan to use this transformation on other variables you can also add a variable suffix. E.g. if you transform your variable using z-scores (more on this in the next tutorial) add _zScore. Now each new variable will have this suffix - Age_zScore, Height_zScore etc.

Now select + Add recode condition

Note: Rather than selecting Create new transform... you can also just select an existing transformation from the list. Jamovi will then apply this transformation to your variable, rather than you having to re-create the conditions. 

You can also edit existing transformations by selecting Edit. To edit the transformation, just follow the steps below

Now you need to add conditions. Jamovi uses simple if ... else statements. Jamovi executes each statement starting from the top. 

You can add as many conditions as you want by selecting + Add recode condition. This will add a new if $source line into the box. remember they will be executed in order.

You now need to populate the boxes with the information. The $source is the variable you want to transform - don't change this. 

Now select one of the following:

• == equal to

• != not equal to

• < Less than

• > Greater than

• >= Greater or equal to

In the next box, you will put your condition e.g. the age you want as the cut-off point. 

After the use, add your new label. If you are using text you must enclose it in '...'

Finally, after the else use box just add the label for the data that does not meet the above conditions. You can leave this blank. 

Follow the above step for each recode condition 

Example:

In our case, we want to create one category for the under 50s and one for the over 50s.

Essentially what we are saying is if someone's age is below 50, label it 'under 50' otherwise label it 'over 50'

In Jamovi it will look like this:

if $source < 50 use 'under 50'

else use 'Over 50'

Voila, you have transformed your first variable

In this example, we will compute the z-scores for age.

Data > Transform > Select Age

Now give the variable a name and description.

Using transform > select Create New Transform...

You can now give this transformation a name, description and suffix. 

Click on Fx > select your function (Z) and double-click

As the $source variable (in this case Age) is already in the field you just have to move the brackets to surround $source.

Your code should look like this:

Z($source)

You have now computed your first variable. You can now use your Standardise Transform on any variable. If you have added a suffix, your new variable will include this in the title e.g. Age_zScores

Here we will rank the Age of participants

Data > Compute 

Give your new variable a name and descriptions

Click Fx > select function (RANKED) > select variable (Age) and double-click on them

If you want to know what a function does click on it once, a description will appear below.

Your text should look like this:

RANK(Age)

You have now created another computed variable which Ranks your participants according to their age.

Follow the step above then choose the SUM function.

Click Fx > select function (SUM) > select your variables and double-click on them > separate each with a comma

If you want to know what a function does click on it once, a description will appear below.

Your text should look like this: 

SUM (Place_World, Understand_Personality)

You could also standardise the output by using the z-scores as well. Then your text would look as follows:

Z(SUM(Place_World, Understand_Personality))

You have now created another computed variable which gives you the sum of the two variables we have selected. 

Data > Filter > Select  your variable (Age)

You can either select your variable by clicking on the fx symbol, then scroll to the variable and double-click on it, or you can type in the variable name. If you are typing in your variable, and the variable has a space, then use '..' around the variable names.

Now use one of the selectors below: 

• == equal to

• != not equal to

• < Less than

• > Greater than

• >= Greater or equal to

Now you can add your conditions in this case < 50.

Your filter should look something like this:

Age < 50 

Here you are telling Jamovi to filter out all rows where this condition is not met e.g. all above the age of 50 are filtered out. 

Voila, you have created your first filter.

The easiest way to work with more than 1 condition is to create another filter. Similar to Transform, Jamovi works through each Filter, so your order is important. 

Each new filter will already exclude the rows filtered out by previous filters. 

To create an additional Filter click on the + to the right of the filter box

Now follow Step 1 for each additional filter.

In our example, we also want to filter out every participant who has 4 or more children.

Our second filter should look something like this:

Household_Dependents < 4 

We have now created a second filter that also filters every participant that is over 50 and has more than 4 household dependents. 

You can easily deactivate filters, hide them or delete them.

Deactivate a filter:  Toggle active >  inactive 

Your filter will remain visible and can be toggled to active at any time.  

Delete Filters: Click on the cross of the filter you want to delete

This will permanently delete your filter.

Make all Filters invisible: Click on the eye symbol on the right side of the filters.

All filters and the filtered data will remain active but will be invisible.