Now that you are familiar with the JASP workspace,
and you know how to set variables, you next need to learn how to select the
cases that you want to analyze, either by filtering out unneeded cases,
or by splitting your analysis into two or more parts.
For this example, we will be using the JASP data file
called "Kitchen Rolls." Click on the main menu icon ->
open -> data library... and choose t-tests. Select the version of
the Kitchen Rolls data set with the JASP icon
in the corner.
So you may be wondering about these kitchen rolls?
Remember that JASP was created in Amsterdam and "kitchen
rolls" is what the Dutch call "paper towels."
They call toilet paper, "bathroom rolls," and they call
cinnamon rolls "kaneelbroodje"... or they would, if the Dutch actually had
cinnamon rolls. I try to stay away from the cinnamon
rolls... don't need any more fat rolls... but about those kitchen rolls
In the dataset we see that there are already two analyses
in this file: a frequentist (or traditional)
independent samples t-test, and a Bayesian
independent samples t-test. Above that is a description of the data in this
file. If you would like to explore Bayesian
statistics a little more, I'd encourage you to open various data
sets and read the notes for the Bayesian and frequentist approaches. For now,
however, I want to clear out these analyses so
that it will be easier for you to see the results in our next example.
Click on the red X to delete anything that you do not need.
And now we will look at the data.
For some analyses, you want to consider only part of your data set.
Perhaps you are interested in only the male or the female respondents?
Or perhaps you have a variable with three categories, but you want to remove
one from the analysis, and only consider the
other two categories. This is the role of filters in JASP.
For SPSS users, this is the same function as the Data -> Select Cases...
command. We select "if condition is satisfied" and tick "If"...
We use the Sex variable and select cases if Sex
equals 'F'. (We must put the F in either single or double quotes,
because this is a string variable.) Click OK. Non-selected cases -
in this example the male respondents - are indicated by the slash.
If we get descriptive statistics for the mean_NEO
variable, only scores for the 77 females will be
calculated.
Now let's do this in JASP. So that you can see the results change
as we apply filters, let's have a table visible. Click on
Descriptives to see the Descriptive Statistics.
We need a nice scale variable, so move mean_NEO into the variables box.
In the results pane, we see the descriptive statistics for all
102 participants. For this example, I will adjust the panes
so that we can see the data and the results. Watch the results
change as we apply filters to the data.
Scroll over and select the variable name for the Sex
variable... we see the categories for this variable.
The filter check mark means that a particular value
IS included in the analysis. If you deselect males,
you see the X that means those values are no longer included in the analysis.
The filter icon appears next to the variable name,
and the scores for males have been grayed out.
For any analysis that you do with this filter on,
your results will only include scores for the 77 females.
Strike that... reverse it... and now only the scores for the 25
males will appear in your analysis.
You can also filter using the pass-through filter tool.
Begin by examining the Condition variable.
Now, this research was done under four conditions.
Perhaps i want to consider only condition 3,
ignoring all others. Click on the funnel to open the pass-through filter by
dragging and clicking, I create the formula
"Condition = 3"
Tick the "apply pass-through filter" bar. Here are descriptive statistics for the
9 males from condition 3.
Ticking the eye icon will hide or show the filtered cases.
Or perhaps i want to consider only conditions 3 and 4,
ignoring 1 and 2. If i create a second filter for
"Condition = 4" I get an error, because no one is in
BOTH condition 3 and 4. To clear the pass-through filter,
double-click on the trash can... do they call this a "bin" in Europe?
I could try to filter only conditions
greater than 2, but that will not work because Condition
is a nominal variable. Reset that, too. So here is how to choose between filters
and pass-through filters: if you are using categorical variables
(nominal and ordinal) then use the filters to
select the categories to include. If you are using scale variables
then you can use mathematical formulas in the pass-through filters.
So save the math for the continuous variables and for
amounts and use filters for categories. Now you can tick the eraser with an asterisk
to remove all filters that have been applied
and now i am back to my original 102 total respondents.
We used a filter to select only males or only females in the data, but what if we
wanted to separate the male and female scores, but still see
them side by side?
In SPSS, this is equivalent to the Split File... command. To split the file,
we organize the group output by the Sex variable.
when we run the descriptive statistics on the mean_NEO variable
we get a separate table for females and males.
Now let's do this in JASP let's split the file in JASP. I have
arranged the panes so that we can see the analysis pane and
the results pane. We are still using the descriptive
statistics. We can see all 102 participants are included in our
analysis. Move the Sex variable into the split box
We have now split the analysis and we can consider categories separately.
At the same time, we can use any categorical variable for the split.
For example, replace Sex with Condition...
Now we have divided our descriptives into four categories,
instead of two. If we add a distribution plot
or any other plot, they will also be presented separately
I want to show you an excellent way to use filters
to specify groups. In the future, we are going to learn about an
independent samples t-test, which tests the mean of two groups.
Now this type of t-test requires only two groups,
not one, not three or more: only two.
In SPSS, we can run an independent samples t-test
using Analyze -> Compare Means
We will use the mean_NEO as our scale-level dependent variable,
and Condition as the independent variable,
or factor. The condition variable has four levels,
but we can specify that we only want to compare groups 1
and 4. Remember that the t-test can only use
two groups. Let's try doing an independent samples t-test in JASP.
We will use the same mean_NEO as our dependent variable,
and use the nominal variable Condition for the groups...we get an
error message about there being more than two groups.
Can you guess why?
Show the data. The Condition variable has four levels or four groups,
we can only use two. If we want to compare only groups 1
and 4, filter out groups 2 and 3
now return to our t-test .The t-test can now
run because we only have two groups in our nominal variable.
If you have followed these first four videos, you are now
familiar with the JASP workspace ,you know how to set
variables, and you know how to do some basic
data management. Our next task is to learn how to create new variables
for the analyses that we will be doing in JASP.
These are tax deductible, right? I mean, i used it for the video, so I can... i can
write this off? i need to call that Legal Eagle guy.