From: Dennis Murphy <djmuser_at_gmail.com>

Date: Fri, 20 May 2011 19:55:08 -0700

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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. Received on Sat 21 May 2011 - 02:57:26 GMT

Date: Fri, 20 May 2011 19:55:08 -0700

Here's one attempt; I only used five of the wafers since you didn't provide any data.

dd <- data.frame(wafer = factor(rep(1:5, each = 6)),

operator = factor(rep(rep(1:3, each = 2), 5)), thickness = c(0.62, 0.66, 0.53, 0.53, 0.51, 0.55, 0.99, 1.00, 1.05, 0.93, 1.05, 1.02, 0.82, 0.81, 0.80, 0.77, 0.90, 0.77, 0.85, 0.89, 0.83, 0.76, 0.79, 0.81, 0.59, 0.48, 0.39, 0.40, 0.46, 0.51))

# Summarize the data to output the mean, sd, min and max of thickness

library(ggplot2)

dsumm <- ddply(dd, .(wafer, operator), summarise, tmean = mean(thickness),

tmin = min(thickness), tmax = max(thickness), tsd = sd(thickness))

# 'Multi-vari' plot:

p1 <- ggplot(dd) +

geom_point(aes(x = wafer, y = thickness)) + geom_errorbar(data = dsumm, aes(x = wafer, y = tmean, ymin = tmin, ymax = tmax), colour = 'blue') + geom_segment(data = dsumm, aes(x = wafer, y = tmean, yend = tmean, xend = as.numeric(wafer) + 0.2), colour = 'blue') + geom_segment(data = dsumm, aes(x = wafer, y = tmean, yend = tmean, xend = as.numeric(wafer) - 0.2), colour = 'blue') + facet_wrap( ~ operator, nrow = 1) + xlab("")

# Standard deviation plot

p2 <- ggplot(dsumm, aes(x = wafer, y = tsd)) +

geom_point(colour = 'blue') + geom_line(aes(group = 1), size = 1, colour = 'blue') +

facet_wrap( ~ operator, nrow = 1)

# Use the gridExtra package to combine the two graphs
library(gridExtra)

grid.arrange(p1, p2)

**HTH,
**

Dennis

On Fri, May 20, 2011 at 4:12 PM, Joseph Boyer <joseph.g.boyer_at_gsk.com> wrote:

> Is there a package in R that can do a variability plot?

*>
**> A variability plot is a kind of categorized dot plot. (If there is a lot of data in each category, box plots are used rather than dot plots.)
**> Usually, the categories are factor level combinations. All the dot plots appear in the same window; below the x-axis a hierarchy of factors
**> shows which dot plot corresponds to which factor-level combination.
**>
**> Examples can be seen
**> http://statsoft.com/support/blog/entryid/64/user-defined-variability-plots/
**> and
**> http://www.public.iastate.edu/~wrstephe/stat495/GaugeRR_WaferThickness_JMPOutput.pdf
**>
**> By reordering the factor names in the function call, the user can reorder the factor level combinations on the graph, making it easier
**> to do the visual comparisons of interest. The user should also have the option to draw line segments at factor level combination means/medians, and to connect the category means/medians to make visual comparison easier.
**>
**> The only softwares which I am aware of which produce such a plot are Statistica and JMP. I have found these plots to be more powerful than
**> lattice-style categorizations in their ability to allow the user to conveniently process experimental data visually.
**>
**> [[alternative HTML version deleted]]
**>
**> ______________________________________________
**> R-help_at_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.
**>
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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. Received on Sat 21 May 2011 - 02:57:26 GMT

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