Plot.Scatterplot.Matrix: Explore data

In NormData: Derivation of Regression-Based Normative Data

Explore data

Description

The function Plot.Scatterplot.Matrix() makes a scatterplot matrix of the specified variables.

Usage

Plot.Scatterplot.Matrix(Dataset, Variables, 
Add.Jitter=0.1, Seed=123, ...)

Arguments

Dataset	The name of the dataset.
Variables	The names of the variables that should be shown in the scatterplot matrix.
Add.Jitter	The amount of jitter (random noise) that should be added to the variables in the scatterplot matrix. Adding a bit of jitter is useful to show the inidividual data points more clearly, especially if several qualitative variables are added in the plot. The specified value Add.Jitter= in the function call determines the amount of jitter (range of values) that is added. For example, when Add.Jitter=0.1, a random value between -0.1 and 0.1 (sampled from a uniform distribution) is added to the datapoints. Default Add.Jitter=0.1.
Seed	The seed that is used when adding jitter. Default Seed=123.
...	Extra graphical parameters to be passed to plot().

Details

For details, see Van der Elst (2023).

Value

No return value, called for side effects.

Author(s)

Wim Van der Elst

References

Van der Elst, W. (2024). Regression-based normative data for psychological assessment: A hands-on approach using R. Springer Nature.

Examples

data(Substitution)

# Make a scatterplot matrix with the variables LDST, 
# Age, Gender and LE in the Substitution dataset
Plot.Scatterplot.Matrix(Dataset = Substitution, 
Variables = c("LDST", "Age", "Gender", "LE"))

NormData documentation built on May 29, 2024, 6:23 a.m.