ancova: 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.

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

Value

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.

Examples

Run this code

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)