Created
September 23, 2012 12:49
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Visually-weighted regression plot, with Zelig
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# A simple approach to visually-weighted regression plots, with Zelig | |
doInstall <- TRUE # Change to FALSE if you don't want packages installed. | |
toInstall <- c("ggplot2", "reshape2", "Zelig") | |
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")} | |
lapply(toInstall, library, character.only = TRUE) | |
# Generate some data: | |
nn <- 1000 | |
myData <- data.frame(X = rnorm(nn), | |
Binary = sample(c(0, 1), nn, replace = T)) | |
myData$Y <- with(myData, X * 2 + Binary * 10 + rnorm(nn, sd = 10)) | |
myData$Y <- (myData$Y > 1) * 1 | |
head(myData) | |
# Model, using Zelig | |
myModel <- zelig(Y ~ X + Binary, model="logit", data=myData) | |
# Simulate from model, using Zelig | |
rangeX <- with(myData, seq(min(X, na.rm = T), max(X, na.rm = T), length.out = 100)) | |
lowScenario <- setx(myModel, X = rangeX, Binary = 0) | |
highScenario <- setx(myModel, X = rangeX, Binary = 1) | |
simulatedScenarios <- sim(myModel, x = lowScenario, x1 = highScenario) | |
# Make a tall data.frame from the Zelig simulation object | |
toReshape <- data.frame(x = simulatedScenarios[[2]][, "X"], | |
t(simulatedScenarios[[6]]$ev)) | |
longEV <- melt(toReshape, id.vars = "x") | |
toReshape2 <- data.frame(x = simulatedScenarios[[2]][, "X"], | |
t(simulatedScenarios[[6]]$fd) + t(simulatedScenarios[[6]]$ev)) | |
longFD <- melt(toReshape2, id.vars = "x") | |
longEV$Setting <- "Minimum" | |
longFD$Setting <- "Maximum" | |
longEV <- data.frame(rbind(longEV, longFD)) | |
# Plot | |
zp1 <- ggplot(data = longEV, | |
aes(x = x, y = value, group = paste(variable, Setting), colour = factor(Setting))) | |
zp1 <- zp1 + geom_line(alpha = I(1/sqrt(nrow(simulatedScenarios[[6]]$ev)))) | |
zp1 <- zp1 + scale_x_continuous("X-axis label", expand = c(0, 0)) | |
zp1 <- zp1 + scale_y_continuous("Y-axis label", limits = c(0, 1), expand = c(0, 0)) | |
zp1 <- zp1 + scale_colour_brewer(palette="Set1", labels = c("High", "Low")) # Change colour palette | |
zp1 <- zp1 + guides(colour = guide_legend("First-difference\nvariable", | |
override.aes = list(alpha = 1))) # Avoid an alpha-related legend problem | |
zp1 <- zp1 + ggtitle("Plot title") | |
zp1 <- zp1 + theme_bw() | |
print(zp1) # This might take a few seconds... |
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