[R] Variability plot in R

[Dennis Murphy]

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.
>
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>
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