ancova: Robust ANCOVA

In WRS2: A Collection of Robust Statistical Methods

Robust ANCOVA

Description

This function computes robust ANCOVA for 2 independent groups and one covariate. It compares trimmed means. No parametric assumption (e.g. homogeneity) is made about the form of the regression lines. A running interval smoother is used. A bootstrap version which computes confidence intervals using a percentile t-bootstrap is provided as well.

Usage

ancova(formula, data, tr = 0.2, fr1 = 1, fr2 = 1, pts = NA, ...)

ancboot(formula, data, tr = 0.2, nboot = 599, fr1 = 1, fr2 = 1, pts = NA, ...)

Arguments

formula	an object of class formula.
data	an optional data frame for the input data.
tr	trim level for the mean.
fr1	values of the span for the first group (1 means unspecified)
fr2	values of the span for the second group (1 means unspecified)
pts	can be used to specify the design points where the regression lines are to be compared; if NA design points are chosen.
nboot	number of bootstrap samples
...	currently ignored.

Value

Returns an object of class ancova containing:

evalpts	covariate values (including points close to these values) where the test statistic is evaluated
n1	number of subjects at evaluation point (first group)
n2	number of subjects at evaluation point (first group)
trDiff	trimmed mean differences
se	standard errors for trimmed mean differences
ci.low	lower confidence limit for trimmed mean differences
ci.hi	upper confidence limit for trimmed mean differences
test	values of the test statistic
crit.vals	critical values
p.vals	p-values
fitted.values	fitted values from interval smoothing
call	function call

References

Wilcox, R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Elsevier.

See Also

t2way

Examples

head(invisibility)
ancova(mischief2 ~ cloak + mischief1, data = invisibility)

## specifying covariate evaluation points
ancova(mischief2 ~ cloak + mischief1, data = invisibility, pts = c(3, 4, 8, 1))

## bootstrap version
ancboot(mischief2 ~ cloak + mischief1, data = invisibility)

WRS2 documentation built on Nov. 2, 2023, 6:25 p.m.