ancova | R Documentation |
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.
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, ...)
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 |
nboot |
number of bootstrap samples |
... |
currently ignored. |
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 |
Wilcox, R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Elsevier.
t2way
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)
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