theta_plot {dynr} | R Documentation |
A function to plot simple slopes and region of significance.
theta_plot(.lm, predictor, moderator, alpha = 0.05, jn = F, title0,
predictorLab, moderatorLab)
.lm |
A regression object from running a linear model of the form: lm(y~ x1+x2+x1:x2), yielding: y = b0 + b1*x1 + b2*x2 + b3*x1*x2 + residual. In this case, one may rewrite the lm as y = b0 + (b1+b3*x2)*x1 + b2*x2 + residual, where (b1+b3*x2) is referred to as the simple slope of x1, x1 is the predictor, and x2 is the moderator whose values yield different simple slope values for x1. |
predictor |
The independent variable for which simple slope is requested |
moderator |
The moderator whose values affect the simple slopes of the predictor. Appears on the horizontal axis. |
alpha |
The designated alpha level for the Johnson-Neyman technique |
jn |
A binary flag requesting the Johnson-Neyman test (T or F) |
title0 |
Title for the plot |
predictorLab |
Label for the predictor |
moderatorLab |
Label for the moderator |
A region of significance plot with simple slopes of the predictor on the vertical axis, and values of the moderator on the horizontal axis.
Adapted from functions written by Marco Bachl to perform the Johnson-Neyman test and produce a plot of simple slopes and region of significance available at: https://rpubs.com/bachl/jn-plot
# g = lm(y~x1:x2,data=data)
# theta_plot(g, predictor = "x1", moderator = "x2",
# alpha = .05, jn = T, title0=" ",
# predictorLab = "x1", moderatorLab = "x2")