WRS2 (version 0.3-1)

ancova: Robust ANCOVA for 2 independent groups and one covariate.

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, sm = FALSE, fr1 = 1, fr2 = 1, pr = TRUE, pts = NA)
ancboot(formula, data, tr = 0.2, nboot = 599, sm = FALSE, fr1 = 1, fr2 = 1, 
pr = TRUE, pts = NA)

Arguments

formula

an object of class formula.

data

an optional data frame for the input data.

tr

trim level for the mean.

sm

if TRUE it create smooths using bootstrap bagging.

fr1

values of the span for the first group (1 means unspecified)

fr2

values of the span for the second group (1 means unspecified)

pr

if TRUE confidence intervals are adjusted to control the probability of at least one Type I error (but p-values are not)

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

• 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
• 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(formula = mischief2 ~ cloak + mischief1, data = invisibility, pts = c(3, 4, 8, 1))

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