Hello all, I'm trying to plot the effects of variables estimated by a regression model fit individually, and for categorical predictors, the independent variable shows up on the y-axis, with the dependent variable on the x-axis. Is there a way to prevent this reversal?
Sample code with dummy data: # make dummy data set.seed(1) x1 <- runif(200) x2 <- sample(c(1,2),200, TRUE) x3 <- sample(c(0,1),200,T) x4 <- runif(200) # the dependent variable: distance <- (x1/3 + x2 + rnorm(200)^2 - x3 - x4/2) # factor two vars, and add to datadist: x3 <- factor(x3) x2 <- factor(x2) d <- datadist(x1,x2,x3,x4) options(datadist="d") # Make a simple model: f <- ols(distance ~ x1 + x2 + x4+ x3, x=T) # plot variable effect of a categorical variable: plot(Predict(f, x2)) ^ above step generates a plot with x2 on the y-axis and distance on the x-axis, which is the opposite of what I'm aiming for. The continuous variables do not have this problem; nor does the plot(Predict(f)) function to plot all of the effects at once. Thank you so much in advance for your replies! My apologies if this question has been answered already; I've tried searching to no avail. Best, Stephanie (Stanford University, Department of Linguistics) -- View this message in context: http://r.789695.n4.nabble.com/rms-plot-Predict-question-swapping-x-and-y-axis-for-categorical-predictors-tp4646891.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
