Plot jnt Object
# S3 method for jnt plot(x, reg_lty = 1, jnt_lty = 2, col_signif = "red", plot_range = TRUE, ...)
Arguments
| x | Object of class |
|---|---|
| reg_lty | Line type for regression lines. Defaults to 1. |
| jnt_lty | Line type for range of insignificant differences. Defaults to 2. |
| col_signif | Color for bars denoting range of insignificance. Defaults to "red." |
| plot_range | logical. If |
| ... | Additional parameters passed to ggplot (e.g., lwd, pch, xlab, ylab). |
Details
Plot object returned by jnt.
Author
Kevin Middleton middletonk@missouri.edu
Examples
example(jnt) #> #> jnt> # Simulate data #> jnt> set.seed(1234) #> #> jnt> n <- 50 #> #> jnt> x1 <- rnorm(n) #> #> jnt> y1 <- x1 + rnorm(n, sd = 0.2) #> #> jnt> x2 <- rnorm(n) #> #> jnt> y2 <- 1.25 * x2 + rnorm(n, sd = 0.2) #> #> jnt> df1 <- data.frame(x = x1, y = y1) #> #> jnt> df2 <- data.frame(x = x2, y = y2) #> #> jnt> (jnt.out <- jnt(df1, df2)) #> Fitting with OLS #> Assuming x variable is column 1, and y is column 2. #> #> Johnson-Neyman Technique #> #> Alpha = 0.05 #> #> Data 1: #> Slope 0.9853 #> Intercept 0.02126 #> #> Data 2: #> Slope 1.182 #> Intercept 0.01386 #> #> Region of non-significant slope difference #> Lower: -0.5258 #> Upper: 0.8701 #> #> #> jnt> plot(jnt.out) #> `geom_smooth()` using formula 'y ~ x'