# intr.plot.2d: Plotting Conditional Regression Lines with Interactions in... In MBESS: The MBESS R Package

 intr.plot.2d R Documentation

## Plotting Conditional Regression Lines with Interactions in Two Dimensions

### Description

To plot regression lines for one two-way interactions, holding one of the predictors (in this function, z) at values -2, -1, 0, 1, and 2 standard deviations above the mean.

### Usage

``````
intr.plot.2d(b.0, b.x, b.z, b.xz,x.min=NULL, x.max=NULL, x=NULL,
n.x=50, mean.z=NULL, sd.z=NULL, z=NULL,xlab="Value of X",
ylab="Dependent Variable", sd.plot=TRUE, sd2.plot=TRUE, sd_1.plot=TRUE,
sd_2.plot=TRUE, type.sd=2, type.sd2=3, type.sd_1=4, type.sd_2=5,
legend.pos="bottomright", legend.on=TRUE, ... )
``````

### Arguments

 `b.0` the intercept `b.x` regression coefficient for predictor x `b.z` regression coefficient for predictor z `b.xz` regression coefficient for the interaction of predictors x and z `x.min,x.max` the range of x used in the plot `x` a specific predictor vector x, used instead of `x.min` and `x.max` `n.x` number of elements in predictor vector x `mean.z` mean of predictor z `sd.z` standard deviation of predictor z `z` a specific predictor vector z, used instead of `z.min` and `z.max` `xlab` title for the axis which the predictor x is on `ylab` title for the axis which the dependent y is on `sd.plot, sd2.plot, sd_1.plot, sd_2.plot` whether or not to plot the regression line holding z at values 1, 2, -1, and -2 standard deviations above the mean, respectively. Default values are all `TRUE`. `type.sd, type.sd2, type.sd_1, type.sd_2` types of lines to be plotted holding z at values 1, 2, -1, and -2 standard deviations above the mean, respectively. Default are line type 2,3,4, and 5, respectively. `legend.pos` position of the legend; possible options are `"bottomright"`, `"bottom"`, `"bottomleft"`, `"left"`, `"center"`, `"right"`, `"topleft"`, `"top"`, and `"topright"`. `legend.on` whether or not to show the legend `...` allows one to potentially include parameter values for inner functions

### Details

To input the predictor x, one can use either the limits of x (`x.max` and `x.min`) , or a specific vector x (`x`). To input the predictor z, one can use either the mean and standard deviation of z (`mean.z` and `sd.z` ), or a specific vector z (`z`).

### Note

Sometimes some of the regression lines are outside the default scope of the coordinates and thus cannot be seen; in such situations, one needs to, by entering additional arguments, adjust the scope to let proper sections of regression lines be seen. Refer to examples below for more details.

### Author(s)

Keke Lai, Ken Kelley (University of Notre Dame; KKelley@ND.Edu)

### References

Cohen, J., Cohen, P., West, S. G. and Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Erlbaum.

`intr.plot`

### Examples

``````## A situation where one regression line is outside the default scope of the coordinates
intr.plot.2d(b.0=16, b.x=2.2, b.z=2.6, b.xz=.4, x.min=0, x.max=20, mean.z=0, sd.z=3)

## Adjust the scope of x and y axes so that proper sections of regression lines can be seen
intr.plot.2d(b.0=16, b.x=2.2, b.z=2.6, b.xz=.4, x.min=0, x.max=50, mean.z=0,
sd.z=3, xlim=c(0,50), ylim=c(-20,100) )

## Use specific vector(s) to define the predictor(s)
intr.plot.2d(b.0=16, b.x=2.2, b.z=2.6, b.xz=.4, x=c(1:10), z=c(0,2,4,6,8,10))

intr.plot.2d(b.0=16, b.x=2.2, b.z=2.6, b.xz=.4, x.min=0, x.max=20,
z=c(1,3,6,7,9,13,16,20), ylim=c(0,100))

## Change the position of the legend so that it does not block regression lines
intr.plot.2d(b.0=10, b.x=-.3, b.z=1, b.xz=.5, x.min=0, x.max=40, mean.z=-5, sd.z=3,
ylim=c(-100,100),legend.pos="topright" )

``````

MBESS documentation built on Oct. 26, 2023, 9:07 a.m.