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@dsparks /SmoothCoefficientPlot.R
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ggplot2 regression coefficient plot, intervals smoothed out to transparent
SmoothCoefficientPlot <- function(models, modelnames = "", removeintercept = FALSE){
# models must be a list()
Alphas <- seq(1, 99, 2) / 100
Multiplier <- qnorm(1 - Alphas / 2)
zzTransparency <<- 1/(length(Multiplier)/4)
CoefficientTables <- lapply(models, function(x){summary(x)$coef})
TableRows <- unlist(lapply(CoefficientTables, nrow))
if(modelnames[1] == ""){
ModelNameLabels <- rep(paste("Model", 1:length(TableRows)), TableRows)
} else {
ModelNameLabels <- rep(modelnames, TableRows)
}
MatrixofModels <- cbind(do.call(rbind, CoefficientTables), ModelNameLabels)
if(removeintercept == TRUE){
MatrixofModels <- MatrixofModels[!rownames(MatrixofModels) == "(Intercept)", ]
}
MatrixofModels <- data.frame(cbind(rownames(MatrixofModels), MatrixofModels))
MatrixofModels <- data.frame(cbind(MatrixofModels, rep(Multiplier, each = nrow(MatrixofModels))))
colnames(MatrixofModels) <- c("IV", "Estimate", "StandardError", "TValue", "PValue", "ModelName", "Scalar")
MatrixofModels$IV <- factor(MatrixofModels$IV, levels = MatrixofModels$IV)
MatrixofModels[, -c(1, 6)] <- apply(MatrixofModels[, -c(1, 6)], 2, function(x){as.numeric(as.character(x))})
MatrixofModels$Emphasis <- by(1 - seq(0, 1, length = length(Multiplier) + 1)[-1], as.character(round(Multiplier, 5)), mean)[as.character(round(MatrixofModels$Scalar, 5))]
OutputPlot <- qplot(data = MatrixofModels, x = IV, y = Estimate,
ymin = Estimate - Scalar * StandardError, ymax = Estimate + Scalar * StandardError,
ylab = NULL, xlab = NULL, alpha = I(zzTransparency), colour = I(gray(0)), geom = "blank")
OutputPlot <- OutputPlot + geom_hline(yintercept = 0, lwd = I(7/12), colour = I(hsv(0/12, 7/12, 7/12)), alpha = I(5/12))
OutputPlot <- OutputPlot + geom_linerange(data = MatrixofModels, aes(size = 1/Emphasis), alpha = I(zzTransparency), colour = I(gray(0)))
OutputPlot <- OutputPlot + scale_size_continuous(legend = FALSE)
OutputPlot <- OutputPlot + facet_grid(~ ModelName) + coord_flip() + geom_point(aes(x = IV, y = Estimate), colour = I(gray(0))) + theme_bw()
return(OutputPlot)
}
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