stripChart.RdstripChart is a modification of the R function stripchart.
It is a generic function used to produce one dimensional scatter
plots (or dot plots) of the given data, along with text indicating sample size and
estimates of location (mean or median) and scale (standard deviation
or interquartile range), as well as confidence intervals for the population
location parameter.
One dimensional scatterplots are a good alternative to boxplots
when sample sizes are small or moderate. The function invokes particular
methods which depend on the class of the first argument.
stripChart(x, ...)
# S3 method for class 'formula'
stripChart(x, data = NULL, dlab = NULL,
subset, na.action = NULL, ...)
# Default S3 method
stripChart(x,
method = ifelse(paired && paired.lines, "overplot", "stack"),
seed = 47, jitter = 0.1 * cex, offset = 1/2, vertical = TRUE,
group.names, group.names.cex = cex, drop.unused.levels = TRUE,
add = FALSE, at = NULL, xlim = NULL, ylim = NULL, ylab = NULL,
xlab = NULL, dlab = "", glab = "", log = "", pch = 1, col = par("fg"),
cex = par("cex"), points.cex = cex, axes = TRUE, frame.plot = axes,
show.ci = TRUE, location.pch = 16, location.cex = cex,
conf.level = 0.95, min.n.for.ci = 2,
ci.offset = 3/ifelse(n > 2, (n-1)^(1/3), 1), ci.bar.lwd = cex,
ci.bar.ends = TRUE, ci.bar.ends.size = 0.5 * cex, ci.bar.gap = FALSE,
n.text = "bottom", n.text.line = ifelse(n.text == "bottom", 2, 0),
n.text.cex = cex, location.scale.text = "top",
location.scale.digits = 1, nsmall = location.scale.digits,
location.scale.text.line = ifelse(location.scale.text == "top", 0, 3.5),
location.scale.text.cex =
cex * 0.8 * ifelse(n > 6, max(0.4, 1 - (n-6) * 0.06), 1),
p.value = FALSE, p.value.digits = 3, p.value.line = 2, p.value.cex = cex,
group.difference.ci = p.value, group.difference.conf.level = 0.95,
group.difference.digits = location.scale.digits,
ci.and.test = "parametric", ci.arg.list = NULL, test.arg.list = NULL,
alternative = "two.sided", plot.diff = FALSE, diff.col = col[1],
diff.method = "stack", diff.pch = pch[1], paired = FALSE, paired.lines = paired,
paired.lty = 1:6, paired.lwd = 1, paired.pch = 1:14, paired.col = NULL,
diff.name = NULL, diff.name.cex = group.names.cex, sep.line = TRUE,
sep.lty = 2, sep.lwd = cex, sep.col = "gray", diff.lim = NULL,
diff.at = NULL, diff.axis.label = NULL,
plot.diff.mar = c(5, 4, 4, 4) + 0.1, ...)the data from which the plots are to be produced. In the default method the data can be
specified as a list or data frame where each component is numeric, a numeric matrix,
or a numeric vector. In the formula method, a symbolic specification of the form
y ~ g can be given, indicating the observations in the vector y are to be
grouped according to the levels of the factor g (the form y ~ 1 indicates
no grouping). NAs are allowed in the data.
NOTE: When the formula method is used and the argument paired=TRUE (see below),
the data in the vector y must have the same number of observations for each level
of the factor g and for each level sorted in the same way according to the
pairing variable.
for the formula method, a data.frame (or list) from which the variables in x
should be taken.
for the formula method, an optional vector specifying a subset of observations to be used for plotting.
for the formula method, a function which indicates what should happen when the data
contain NAs. The default is to ignore missing values in either the response or
the group.
additional parameters passed to the default method, or by it to plot,
points, axis, and title to control the
appearance of the plot.
the method to be used to separate coincident points. When method="stack"
coincident points are stacked, when method="jitter" coincident points are
jittered, and when method="overplot" coincident points are overplotted.
When there are 2 groups and paired=TRUE and paired.lines=TRUE the
default value is method="overplot", otherewise the default method is
method="stack" (which differs from the default value for the R function
stripchart, which uses method="overplot" by default).
when method="jitter" is used, the argument seed is passed to
the R function set.seed. Since jittering depends on the
R random number generator, using the same value of seed each time
the same data are plotted with stripChart ensures that the resulting
plot is the same.
when method="jitter" is used, jitter gives the amount of jittering applied.
when stacking is used, points are stacked this many line-heights (symbol widths) apart.
when vertical=TRUE (the default), the plots are drawn vertically rather than horizontally.
group labels which will be printed alongside (or underneath) each plot.
numeric scalar indicating the amount by which the group labels should be scaled
relative to the default (see the help file for plot.default).
The default is the current value of the graphics parameter cex.
when drop.unused.levels=TRUE, groups with no observations are dropped.
logical, if true add the chart to the current plot.
numeric vector giving the locations where the charts should be drawn,
particularly when add=TRUE; defaults to 1:n where n
is the number of groups.
plot limits: see plot.window.
labels: see title.
alternate way to specify axis labels. The dlab and glab labels may be used
instead of xlab and ylab if those are not specified. dlab applies
to the continuous data axis (the \(y\)-axis unless vertical=FALSE),
and glab to the group axis.
on which axes to use a log scale: see plot.default.
Graphical parameters: see par.
Sets the cex value for the points plotted.
Axis control: see plot.default.
logical scalar indicating whether to plot the confidence interval. The default is
show.ci=TRUE.
integer indicating which plotting character to use to indicate the estimate of location
(mean or median) for each group (see the help file for plot.default).
The default is location.pch=16, a filled circle.
numeric scalar giving the amount by which the plotting characters indicating the
estimate of location for each group should be scaled relative to the default
(see the help file for plot.default). The default is the current
value of the graphics parameter cex.
numeric scalar between 0 and 1 indicating the confidence level associated with the
confidence interval for the group location (population mean or median).
The default value is conf.level=0.95.
integer indicating the minimum sample size required in order to plot a confidence interval
for the group location. The default value is min.n.for.ci=2.
numeric scalar or vector of length equal to the number of groups (n) in units of
cex indicating the amount of space between the line showing the confidence interval
and tick mark associated with a particular group. The default value depends on the number of
groups and is given by 3/ifelse(n > 2, (n-1)^(1/3), 1).
numeric scalar indicating the line width for the confidence interval bars.
The default is the current value of the graphics parameter cex.
logical scalar indicating whether to add flat ends to the confidence interval bars.
The default value is ci.bar.ends=TRUE.
numeric scalar in units of cxy indicating the size of confidence interval
bar ends. The default value is half of the current value of cex.
logical scalar indicating with to add a gap between the estimate of group location and the
confidence interval bar. The default value is ci.bar.gap=FALSE.
character string indicating whether and where to indicate the sample size for each group.
Possible values are "bottom" (the default), "top", and "none".
integer indicating on which plot margin line to show the sample sizes for each group. The
default value is n.text.line=2 when n.text="bottom" and 0 otherwise.
numeric scalar giving the amount by which the text indicating the sample size for
each group should be scaled relative to the default (see the help file for plot.default). The default is the current value of the graphics
parameter cex.
character string indicating whether and where to indicate the estimates of location
(mean or median) and scale (standard deviation or interquartile range) for each group.
Possible values are "top" (the default), "bottom", and "none".
integer indicating the number of digits to round the estimates of location and scale. The
default value is location.scale.digits=1.
integer passed to the function format indicating the the minimum
number of digits to the right of the decimal point for the estimates of location
and scale. The default value is the value of location.scale.digits, which
forces all estimates of location and scale have the same number of digits to the
right of the decimal point (including, possibly, trailing zeros). To omit trailing zeros,
set nsmall=0.
integer indicating on which plot margin line to show the estimates of location and scale
for each group. The default value is location.scale.text.line=0 when n.text="top" and 3.5 otherwise.
numeric scalar giving the amount by which the text indicating the estimates of
location and scale for each group should be scaled relative to the default
(see the help file for plot.default). The default depends on the
number of groups and is given by
cex * 0.8 * ifelse(n > 6, max(0.4, 1 - (n-6) * 0.06), 1),
where cex denotes the current value of the graphics parameter cex.
logical scalar indicating whether to show the p-value associated with testing whether all groups
have the same population location. The default value is p.value=FALSE.
The p-value is displayed at the top of the graph.
integer indicating the number of digits to round to when displaying the p-value associated with
the test of equal group locations. The default value is p.value.digits=3.
integer indicating on which plot margin line to show the p-value associated with the test of
equal group locations. The default value is p.value.line=2.
numeric scalar giving the amount by which the text indicating the p-value associated
with the test of equal group locations should be scaled relative to the default
(see the help file for plot.default).
The default is the current value of the graphics parameter cex.
for the case when there are just 2 groups, a logical scalar indicating whether to display
the confidence interval for the difference between group locations. The default is
the value of the p.value argument. The confidence interval is displayed at the
top of the graph in the format [Lower CI, Upper CI].
for the case when there are just 2 groups, a numeric scalar between 0 and 1
indicating the confidence level associated with the confidence interval for the
difference between group locations. The default is conf.level=0.95.
for the case when there are just 2 groups, an integer indicating the number of digits to
round to when displaying the confidence interval for the difference between group locations.
The default value is group.difference.digits=location.scale.digits.
character string indicating whether confidence intervals and tests should be based on parametric
or nonparametric (ci.and.test="nonparametric") methods.
When ci.and.test="parametric" (the default), confidence intervals for the population mean
are based on the one-sample t-test (see t.test), and the test of group
differences is based on the two-sample t-test if there are two groups and the F-test
(i.e., one-way analysis of variance, see aov) if there are three or more groups.
When ci.and.test="nonparametric", confidence intervals for the population pseudo-median
are based on the Wilcoxon signed rank test (see wilcox.test and page 56 of
Hollander and Wolfe, 1999), and the test of group differences is based on the
Wilcoxon rank sum test if there are two groups (see wilcox.test) and the
Kruskal-Wallis test (see kruskal.test) if there are three or more groups.
an optional list of arguments to pass to the function used to compute confidence intervals.
The default value is ci.arg.list=NULL.
an optional list of arguments to pass to the function used to test for group differences in location.
The default value is test.arg.list=NULL. In particular, in the case when there are two groups,
ci.and.test="parametric", and ci.arg.list is NULL or does not contain a
component specifying the value for var.equal, this argument is updated to include the
component var.equal=TRUE, which is not the default behavior of t.test.
NOTE: If test.arg.list contains a component named "paired", the value of
that component is set to the value of the argument paired (see below).
character string describing the alternative hypothesis for the test of group differences in the
case when there are two groups. Possible values are "two.sided" (the default),
"less", and "greater".
applicable only to the case when there are two groups:
logical scalar indicating whether to plot the confidence interval for the difference between
the groups. The default is plot.diff=FALSE.
When plot.diff=TRUE and paired=FALSE, the confidence interval
for the difference between the two locations is displayed and the right-hand axis
(when vertical=TRUE) or top axis (when vertical=FALSE) is labeled in units of
the confidence interval for the difference between the two locations. If ci.and.test="parametric", the confidence interval for the difference between the
two means is displayed.
If ci.and.test="nonparametric", the confidence interval for the median of the
difference between a sample from the first group and a sample from the second group is displayed
(see the help file for wilcox.test.
When plot.diff=TRUE and paired=TRUE, the paired differences are
displayed and the right-hand axis (when vertical=TRUE) or
top axis (when vertical=FALSE) is labeled in units of the paired differences.
In addition, if show.ci=TRUE, the confidence interval based on the paired
differences is displayed. In this case, if ci.and.test="parametric"
the confidence interval for the mean of the paired differences is displayed, and
if ci.and.test="nonparametric" the confidence interval for the pseudomedian
is displayed (see the help file for wilcox.test.
applicable only to the case when there are two groups and plot.diff=TRUE:
numeric or character scalar indicating what color to use for the confidence interval for
the difference in locations between the two groups. When paired=TRUE, this
argument also controls the color of the paired differences.
The default is diff.col=col[1].
applicable only to the case when there are two groups, plot.diff=TRUE, and paired=TRUE:
the method to be used to separate coincident points for the paired differences.
The default value is diff.method="stack". Other options are diff.method="jitter"
and diff.method="overplot". See the explanation for the argument method above.
applicable only to the case when there are two groups, plot.diff=TRUE, and paired=TRUE:
numeric or character scalar indicating what plotting symbol to use for the paired differences.
The default is diff.pch=pch[1].
applicable only to the case when there are two groups:
logical scalar indicating whether the observations in the first group are paired with those
in the second group. The default is paired=FALSE.
NOTE 1: When the formula method for the argument x is used (see above) and the
argument paired=TRUE, the data in the vector y must have the same number
of observations for each level of the factor g and for each level sorted in the
same way according to the pairing variable.
NOTE 2: If the argument test.arg.list (see above) contains a component named "paired",
the value of that component is set to the value of the argument paired.
applicable only to the case when there are two groups and paired=TRUE:
logical scalar indicating whether to join the paired observations with lines.
The default value is the value of the argument paired.
applicable only to the case when there are two groups, paired=TRUE, and paired.lines=TRUE:
numeric vector indicating the line types to use to join the paired observations with lines.
The default value is paired.lty=1:6.
applicable only to the case when there are two groups, paired=TRUE, and paired.lines=TRUE:
numeric vector indicating the widths of the lines used to join the paired observations with lines.
The default value is paired.lwd=1.
applicable only to the case when there are two groups, paired=TRUE, and paired.lines=TRUE:
numeric vector indicating the plotting characters to use at each end of the lines used to
join the paired observations with lines. The default value is paired.pch=1:14.
applicable only to the case when there are two groups, paired=TRUE, and paired.lines=TRUE:
character or numeric vector indicating the colors for the lines (and plotting characters)
used to join the paired observations with lines. The default value is paired.col=NULL,
in which case the vector becomes c("black", "red", "green3", "blue", "magenta", "darkgreen", "purple", "orange", "darkolivegreen", "steelblue", "darkgray").
applicable only to the case when there are two groups and plot.diff=TRUE:
character scalar indicating the label to use for the confidence interval for the
difference between groups. For the case when paired=TRUE, this label also
describes the paired differences. The default value is diff.name=NULL,
in which case the label is "group 2 - group 1", where group 1 and group 2 denote the names for
the each group. For example, if group 1 is labeled "A" and group 2 is labeled "B", then
the default value is diff.name="B-A".
applicable only to the case when there are two groups and plot.diff=TRUE:
numeric scalar indicating the amount by which the label for group differences
should be scaled relative to the default (see the help file for plot.default).
The default value is diff.name.cex=group.names.cex.
applicable only to the case when there are two groups and plot.diff=TRUE:
logical scalar indicating whether to draw a line between the strip charts for the two
groups and the confidence interval for the difference between the two groups (and paired
differences when paired=TRUE). The default value is sep.line=TRUE.
applicable only to the case when there are two groups, plot.diff=TRUE, and
sep.line=TRUE:
numeric scalar indicating the line type to use for the line drawn between the strip charts
for the two groups and the confidence interval for the difference between the two groups.
The default value is sep.lty=2.
applicable only to the case when there are two groups, plot.diff=TRUE, and
sep.line=TRUE:
numeric scalar indicating the line width to use for the line drawn between the strip charts
for the two groups and the confidence interval for the difference between the two groups.
The default value is the current value of the graphics parameter cex.
applicable only to the case when there are two groups, plot.diff=TRUE, and
sep.line=TRUE:
numeric or character scalar indicating the color of the line drawn between the strip charts
for the two groups and the confidence interval for the difference between the two groups.
The default value is sep.col="gray".
applicable only to the case when there are two groups and plot.diff=TRUE:
numeric vector of length 2 indicating the limits to use for the axis associated with the
confidence interval for the difference between the two groups.
When paired=FALSE, the default value is the range of the y-axis, but centered at
the mean of the confidence interval for the difference in locations.
When paired=TRUE, the default value is range(pretty(c(X, range(CI)))) where
X denotes the vector containing the paired differences.
applicable only to the case when there are two groups and plot.diff=TRUE:
numeric vector indicating the locations of the tick marks for the axis associated with the
confidence interval for the difference between groups (see the explanation for the argument
at in the help file for axis). The default value is diff.at=NULL,
in which case default values are used for the locations of the tick marks.
applicable only to the case when there are two groups and plot.diff=TRUE:
character string indicating the label to use for the axis associated with the
confidence interval for the difference between groups. When paired=FALSE the
default value is "Difference Between Groups", and when paired=TRUE the
default value is "Paired Difference".
applicable only to the case when there are two groups, plot.diff=TRUE, and add=FALSE:
numeric vector of length 4 indicating the number of lines in the plotting margins
(see the explanation for the argument mar in the help file for par).
The default value is plot.diff.mar = c(5, 4, 4, 4) + 0.1.
stripChart invisibly returns a list with the following components:
numeric vector of values on the group axis (the \(x\)-axis unless
vertical=FALSE) indicating the centers of the groups.
a matrix with the number of rows equal to the number of groups and six columns indicating the sample size of the group (N), the estimate of the group location parameter (Mean or Median), the estimate of the group scale (SD or IQR), the lower confidence limit for the group location parameter (LCL), the upper confidence limit for the group location parameter (UCL), and the confidence level associated with the confidence interval (Conf.Level)
In addition, if the argument p.value=TRUE and/or 1) there are two groups and 2) plot.diff=TRUE,
the list also includes these components:
numeric scalar indicating the p-value associated with the test of equal group locations.
numeric vector of two elements indicating the confidence interval for the difference between the group locations. Only present when there are two groups.
Hollander, M., and D.A. Wolfe. (1999). Nonparametric Statistical Methods. Second Edition. John Wiley and Sons, New York.
Millard, S.P., and N.K. Neerchal. (2001). Environmental Statistics with S-PLUS. CRC Press, Boca Raton, FL.
Zar, J.H. (2010). Biostatistical Analysis. Fifth Edition. Prentice-Hall, Upper Saddle River, NJ.
#------------------------
# Two Independent Samples
#------------------------
# The guidance document USEPA (1994b, pp. 6.22--6.25)
# contains measures of 1,2,3,4-Tetrachlorobenzene (TcCB)
# concentrations (in parts per billion) from soil samples
# at a Reference area and a Cleanup area. These data are strored
# in the data frame EPA.94b.tccb.df.
#
# First create one-dimensional scatterplots to compare the
# TcCB concentrations between the areas and use a nonparametric
# test to test for a difference between areas.
dev.new()
stripChart(TcCB ~ Area, data = EPA.94b.tccb.df, col = c("red", "blue"),
p.value = TRUE, ci.and.test = "nonparametric",
ylab = "TcCB (ppb)")
#> Warning: cannot compute exact p-value with ties
#> Warning: cannot compute exact confidence interval with ties
#----------
# Now log-transform the TcCB data and use a parametric test
# to compare the areas.
dev.new()
stripChart(log10(TcCB) ~ Area, data = EPA.94b.tccb.df, col = c("red", "blue"),
p.value = TRUE, ylab = "log10 [ TcCB (ppb) ]")
#----------
# Repeat the above procedure, but also plot the confidence interval
# for the difference between the means.
dev.new()
stripChart(log10(TcCB) ~ Area, data = EPA.94b.tccb.df, col = c("red", "blue"),
p.value = TRUE, plot.diff = TRUE, diff.col = "black",
ylab = "log10 [ TcCB (ppb) ]")
#----------
# Repeat the above procedure, but allow the variances to differ.
dev.new()
stripChart(log10(TcCB) ~ Area, data = EPA.94b.tccb.df, col = c("red", "blue"),
p.value = TRUE, plot.diff = TRUE, diff.col = "black",
ylab = "log10 [ TcCB (ppb) ]", test.arg.list = list(var.equal = FALSE))
#----------
# Repeat the above procedure, but jitter the points instead of
# stacking them.
dev.new()
stripChart(log10(TcCB) ~ Area, data = EPA.94b.tccb.df, col = c("red", "blue"),
p.value = TRUE, plot.diff = TRUE, diff.col = "black",
ylab = "log10 [ TcCB (ppb) ]", test.arg.list = list(var.equal = FALSE),
method = "jitter", ci.offset = 4)
#----------
# Clean up
#---------
graphics.off()
#====================
#--------------------
# Paired Observations
#--------------------
# The data frame ACE.13.TCE.df contians paired observations of
# trichloroethylene (TCE; mg/L) at 10 groundwater monitoring wells
# before and after remediation.
#
# Create one-dimensional scatterplots to compare TCE concentrations
# before and after remediation and use a paired t-test to
# test for a difference between periods.
ACE.13.TCE.df
#> TCE.mg.per.L Well Period
#> 1 20.900 1 Before
#> 2 9.170 2 Before
#> 3 5.960 3 Before
#> 4 41.500 4 Before
#> 5 34.300 5 Before
#> 6 19.700 6 Before
#> 7 38.900 7 Before
#> 8 8.180 8 Before
#> 9 9.130 9 Before
#> 10 28.500 10 Before
#> 11 0.917 1 After
#> 12 8.770 2 After
#> 13 4.370 3 After
#> 14 4.340 4 After
#> 15 10.700 5 After
#> 16 1.480 6 After
#> 17 0.272 7 After
#> 18 0.520 8 After
#> 19 3.060 9 After
#> 20 1.900 10 After
# TCE.mg.per.L Well Period
#1 20.900 1 Before
#2 9.170 2 Before
#3 5.960 3 Before
#... ...... .. ......
#18 0.520 8 After
#19 3.060 9 After
#20 1.900 10 After
dev.new()
stripChart(TCE.mg.per.L ~ Period, data = ACE.13.TCE.df,
col = c("brown", "green"), p.value = TRUE, paired = TRUE,
ylab = "TCE (mg/L)")
#----------
# Repeat the above procedure, but also plot the confidence interval
# for the mean of the paired differences.
dev.new()
stripChart(TCE.mg.per.L ~ Period, data = ACE.13.TCE.df,
col = c("brown", "green"), p.value = TRUE, paired = TRUE,
ylab = "TCE (mg/L)", plot.diff = TRUE, diff.col = "blue")
#==========
# Repeat the last two examples, but use a one-sided alternative since
# remediation should decrease TCE concentration.
dev.new()
stripChart(TCE.mg.per.L ~ Period, data = ACE.13.TCE.df,
col = c("brown", "green"), p.value = TRUE, paired = TRUE,
ylab = "TCE (mg/L)", alternative = "less",
group.difference.digits = 2)
#----------
# Repeat the above procedure, but also plot the confidence interval
# for the mean of the paired differences.
#
# NOTE: Although stripChart can *report* one-sided confidence intervals
# for the difference between two groups (see above example),
# when *plotting* the confidence interval for the difference,
# only two-sided CIs are allowed.
# Here, we will set the confidence level of the confidence
# interval for the mean of the paired differences to 90%,
# so that the upper bound of the CI corresponds to the upper
# bound of a 95% one-sided CI.
dev.new()
stripChart(TCE.mg.per.L ~ Period, data = ACE.13.TCE.df,
col = c("brown", "green"), p.value = TRUE, paired = TRUE,
ylab = "TCE (mg/L)", group.difference.digits = 2,
plot.diff = TRUE, diff.col = "blue", group.difference.conf.level = 0.9)
#----------
# Clean up
#---------
graphics.off()
#==========
# The data frame Helsel.Hirsch.02.Mayfly.df contains paired counts
# of mayfly nymphs above and below industrial outfalls in 12 streams.
#
# Create one-dimensional scatterplots to compare the
# counts between locations and use a nonparametric test
# to compare counts above and below the outfalls.
Helsel.Hirsch.02.Mayfly.df
#> Mayfly.Count Stream Location
#> 1 12 1 Above
#> 2 15 2 Above
#> 3 11 3 Above
#> 4 41 4 Above
#> 5 106 5 Above
#> 6 63 6 Above
#> 7 296 7 Above
#> 8 53 8 Above
#> 9 20 9 Above
#> 10 110 10 Above
#> 11 429 11 Above
#> 12 185 12 Above
#> 13 9 1 Below
#> 14 9 2 Below
#> 15 38 3 Below
#> 16 24 4 Below
#> 17 48 5 Below
#> 18 17 6 Below
#> 19 11 7 Below
#> 20 41 8 Below
#> 21 14 9 Below
#> 22 60 10 Below
#> 23 53 11 Below
#> 24 124 12 Below
# Mayfly.Count Stream Location
#1 12 1 Above
#2 15 2 Above
#3 11 3 Above
#... ... .. .....
#22 60 10 Below
#23 53 11 Below
#24 124 12 Below
dev.new()
stripChart(Mayfly.Count ~ Location, data = Helsel.Hirsch.02.Mayfly.df,
col = c("green", "brown"), p.value = TRUE, paired = TRUE,
ci.and.test = "nonparametric", ylab = "Number of Mayfly Nymphs")
#> Warning: cannot compute exact p-value with ties
#> Warning: cannot compute exact confidence interval with ties
#> Warning: cannot compute exact p-value with ties
#> Warning: cannot compute exact confidence interval with ties
#----------
# Repeat the above procedure, but also plot the confidence interval
# for the pseudomedian of the paired differences.
dev.new()
stripChart(Mayfly.Count ~ Location, data = Helsel.Hirsch.02.Mayfly.df,
col = c("green", "brown"), p.value = TRUE, paired = TRUE,
ci.and.test = "nonparametric", ylab = "Number of Mayfly Nymphs",
plot.diff = TRUE, diff.col = "blue")
#> Warning: cannot compute exact p-value with ties
#> Warning: cannot compute exact confidence interval with ties
#> Warning: cannot compute exact p-value with ties
#> Warning: cannot compute exact confidence interval with ties
#----------
# Clean up
#---------
graphics.off()