Performing multiple analyses

Comparison tests

For tests where the Y variables are compared to X variables you can use Block mode to choose how the multiple Y variables are compared with the various X variables.

There are three possible options to choose from, although OxonStat will only present you with the ones that are relevant for your selected variables and test.

One to One

Should the number of variables in each set be equal, then the One to One Block Mode option may be used. For example:

In this mode:

The first Y variable is analysed with the first X variable (in our example Weight vs Height)
The second Y variable is analysed with the second X variable (in our example Height vs Age)
The third Y variable is analysed with the third X variable (in our example Age vs Gender)
...and so on, until all variables are used.

The number of analyses produced will be equal to the number of Y variables.

For tests where the Y variable and X variable cannot be the same, such as the Paired-t test, these pairs will be removed and the number of tests will be reduced.

Many to Many

Where the number of Y variables or number of X variables sets have more than one variable. For example:

In this mode:

In this mode the first Y variable is analysed with each X variable in turn (in our example Weight vs Height, Weight vs Age, Weight vs Gender)
The second Y variable is analysed with each X variable in turn (in our example Height vs Height, Height vs Age, Height vs Gender)
The third Y variable is analysed with each X variable in turn (in our example Age vs Height, Age vs Age, Age vs Gender)
...and so on until all Y variables are used

The analyses produced will be equal to the number of Y variables multiplied by the number of X variables.

Exclusions

Certain tests will refuse to compare a variable with itself, since the results would have no meaning. For example Paired-t, Wilcoxon Signed Rank, Correlation / Regression and Spearman Rank. For these tests if the Y variable and X variable is a match the test will be excluded. For example:

In this example, the comparisons would be:

Weight vs Height
Weight vs Age
Height vs Height would be excluded as the variables match
Height vs Age

The analyses produced will be equal to the number of Y variables multiplied by the number of X variables, minus the number of variables that are set as both Y and X.

Tip

It is possible to generate enormous numbers of analyses (and printouts!) using Many to Many Block Mode option.

One to Many

This special mode is only available to the Multiple Linear Regression test. In this mode:

The first Y variable is analysed with all X variables at the same time.
The second Y variable is analysed with all X variables at the same time.
...and so on, until all Y variables are used.