s20x (version 3.1-40)

onewayPlot: One-way Analysis of Variance Plot

Description

Displays stripplot/boxplot of the reponse variable with intervals by factor levels. It is used as part of a one-way ANOVA analysis.

Usage

onewayPlot(x, ...)
# S3 method for default
onewayPlot(
  x,
  f,
  conf.level = 0.95,
  interval.type = "tukey",
  pooled = TRUE,
  strip = TRUE,
  vert = TRUE,
  verbose = FALSE,
  ylabel = deparse(terms(formula)[[2]]),
  flabel = deparse(terms(formula)[[3]]),
  ...
)
# S3 method for formula
onewayPlot(
  formula,
  data = parent.frame(),
  conf.level = 0.95,
  interval.type = "tukey",
  pooled = TRUE,
  strip = TRUE,
  vert = TRUE,
  verbose = FALSE,
  ylabel = deparse(terms(formula)[[2]]),
  flabel = deparse(terms(formula)[[3]]),
  ...
)
# S3 method for lm
onewayPlot(x, ..., ylabel = nms[1], flabel = nms[2])

Arguments

x

a vector of responses, a formula object or an lm object

...

optional arguments.

f

if x is a vector of responses then f contains the group labels for each observation in x. That is, the ith value in f says which group the ith observation of x belongs to.

conf.level

confidence level of the intervals.

interval.type

three options for intervals appearing on plot: 'hsd','lsd' or 'ci'.

pooled

two options: pooled or unpooled standard deviation used for plotted intervals.

strip

if strip=F, boxplots are displayed instead.

vert

if vert=F, horizontal stripplots are displayed instead (boxplots can only be displayed vertically).

verbose

if true, print intervals on console.

ylabel

can be used to replace variable name of y by another string.

flabel

can be used to replace variable name of f by another string.

formula

a symbolic description of the model to be fit.

data

an optional data frame in which to evaluate the formula.

Methods (by class)

• onewayPlot(default): One-way Analysis of Variance Plot

• onewayPlot(formula): One-way Analysis of Variance Plot

• onewayPlot(lm): One-way Analysis of Variance Plot

See Also

summary1way, t.test.

Examples

##see example in 'summary1way'

##computer data:
data(computer.df)
onewayPlot(score~selfassess, data = computer.df)


##apple data:
data(apples.df)
twosampPlot(Weight~Propagated, data = apples.df)

##oyster data:
data(oysters.df)
onewayPlot(log(Oysters)~Site, data = oysters.df)

##oyster data:
data(oysters.df)
oyster.fit = lm(log(Oysters)~Site, data = oysters.df)
onewayPlot(oyster.fit)