eovcheck {s20x}R Documentation

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 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(object, ...)
## S3 method for class 'formula':
eovcheck (object, data = NULL, xlab = NULL, col = NULL
                            ,smoother = FALSE, twosd = FALSE,  ...)
## S3 method for class 'lm':
eovcheck (object, smoother = FALSE, twosd = FALSE, ...)

Arguments

object A linear model formula. Alternatively, a fitted lm object from a linear model.
data A data frame in which to evaluate the formula.
xlab a title for the x axis: see title.
col a color 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
... Optional arguments

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)

[Package s20x version 3.1-5 Index]