eovcheck: Testing for equality of variance plot

In s20x: Functions for University of Auckland Course STATS 201/208 Data Analysis

Testing for equality of variance plot

Description

Plots the residuals versus the fitted (or predicted) values from a linear model. A horizontal line is drawn at y = 0, reflecting the fact that we expect the residuals to have a mean of zero. An optional lowess line is drawn if smoother is set to TRUE. This can be useful in determining whether a trend still exists in the residuals. An optional pair of lines is drawn at +/- 2 times the standard deviation of the residuals - which is estimated from the Residual Mean Sqare (Within group mean square = WGMS). This can be useful in highlighting potential outliers. If the model has one or two factors and no continous variables, i.e. if it is a oneway or twoway ANOVA model, and levene = TRUE then the P-value from Levene's test for equality variance is displayed in the top left hand corner, as long as the number of observations per group exceeds two.

Usage

eovcheck(x, ...)

## S3 method for class 'formula'
eovcheck(
  x,
  data = NULL,
  xlab = "Fitted values",
  ylab = "Residuals",
  col = NULL,
  smoother = FALSE,
  twosd = FALSE,
  levene = FALSE,
  engine = c("base", "ggplot2"),
  ...
)

## S3 method for class 'lm'
eovcheck(
  x,
  smoother = FALSE,
  twosd = FALSE,
  levene = FALSE,
  engine = c("base", "ggplot2"),
  ...
)

Arguments

x	A linear model formula. Alternatively, a fitted lm object from a linear model.
...	Optional arguments passed to the base plotting engine. Extra arguments are currently ignored by the ggplot2 engine.
data	A data frame in which to evaluate the formula.
xlab	a title for the x axis: see title.
ylab	a title for the y axis: see title.
col	a colour for the lowess smoother line.
smoother	if TRUE then a smoothed lowess line will be added to the plot
twosd	if TRUE then horizontal dotted lines will be drawn at +/-2sd
levene	if TRUE then the P-value from Levene's test for equality of variance is displayed
engine	plotting engine to use. The default, "base", preserves the original base graphics output. Use "ggplot2" for an optional ggplot2 object.

Details

The default base graphics engine preserves the original teaching plot and draws directly on the active graphics device. The optional ggplot2 engine is intended for users who want a reusable plot object for reports or further customisation; it requires ggplot2 to be installed and returns a ggplot object instead of drawing a base graphics side effect.

Value

Draws the residual-versus-fitted diagnostic plot when using the base engine. With engine = "ggplot2", returns a ggplot object.

See Also

levene.test

Examples

# one way ANOVA - oysters
data(oysters.df)
oyster.fit = lm(Oysters ~ Site, data = oysters.df)
eovcheck(oyster.fit)

# Same model as the previous example, but using eovcheck.formula
data(oysters.df)
eovcheck(Oysters ~ Site, data = oysters.df)


# A two-way model without interaction
data(soyabean.df)
soya.fit = lm(yield ~ planttime + cultivar, data = soyabean.df)
eovcheck(soya.fit)

# A two-way model with interaction
data(arousal.df)
arousal.fit = lm(arousal ~ gender * picture, data = arousal.df)
eovcheck(arousal.fit)

# A regression model
data(peru.df)
peru.fit = lm(BP ~ height + weight + age + years, data = peru.df)
eovcheck(peru.fit)


# A time series model
data(airpass.df)
t = 1:144
month = factor(rep(1:12, 12))
airpass.df = data.frame(passengers = airpass.df$passengers, t = t, month = month)
airpass.fit = lm(log(passengers)[-1] ~ t[-1] + month[-1]
                 + log(passengers)[-144], data  = airpass.df)
eovcheck(airpass.fit)

# Optional ggplot2 engine for reusable plot objects
if (requireNamespace("ggplot2", quietly = TRUE)) {
  eovPlot = eovcheck(oyster.fit, engine = "ggplot2")
  class(eovPlot)

  eovcheck(peru.fit, engine = "ggplot2", smoother = TRUE)
  eovcheck(oyster.fit, engine = "ggplot2", twosd = TRUE, levene = TRUE)
}

s20x documentation built on July 1, 2026, 9:06 a.m.