confint_adjust {api2lm} | R Documentation |
Adjust confidence intervals for multiple comparisons
Description
A function to produce adjusted confidence intervals with a family-wise
confidence level of at least level
for
lm
objects (not applicable if no adjustment is used).
Internally, the function is a slight revision of the code
used in the confint.lm
function.
Usage
confint_adjust(object, parm, level = 0.95, method = "none")
Arguments
object |
a fitted model object. |
parm |
a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered. |
level |
the confidence level required. |
method |
A character string indicating the type of
adjustment to make. The default choice is
|
Details
Let a = 1 - level
. Let p
be the number of
estimated coefficients in the fitted model. All intervals are computed
using the formula estimate +/- m * ese
, where
m
is a multiplier and ese
is the estimated
standard error of the estimate
.
method = "none"
(no correction) produces the
standard t-based confidence intervals with multiplier
qt(1 - a/2, df = object$df.residual)
.
method = "bonferroni"
produces Bonferroni-adjusted
intervals that use the multiplier m = qt(1 - a/(2 *
k), df = object$df.residual)
, where k
is the
number of intervals being produced.
method = "wh"
produces Working-Hotelling-adjusted
intervals that are valid for all linear combinations of
the regression coefficients, which uses the multiplier
m = sqrt(p * qf(level, df1 = p, df2 =
object$df.residual))
.
Value
A confint_adjust
object, which is simply a
a data.frame
with columns term
,
lwr
(the lower confidence limit), and upr
(the upper confidence limit).
References
Bonferroni, C. (1936). Teoria statistica delle classi e calcolo delle probabilita. Pubblicazioni del R Istituto Superiore di Scienze Economiche e Commericiali di Firenze, 8, 3-62.
Working, H., & Hotelling, H. (1929). Applications of the theory of error to the interpretation of trends. Journal of the American Statistical Association, 24(165A), 73-85. doi:10.1080/01621459.1929.10506274
Kutner, M. H., Nachtsheim, C. J., Neter, J., & Li, W. (2004). Applied Linear Statistical Models, 5th edition. New York: McGraw-Hill/Irwin. (p. 230)
See Also
Examples
## an extension of the documentation for confint.lm
fit <- lm(100/mpg ~ disp + hp + wt + am, data = mtcars)
# standard intervals
confint_adjust(fit)
# bonferroni-adjusted intervals
(cib <- confint_adjust(fit, method = "b"))
# plot results
plot(cib)
plot(cib, parm = c("hp", "disp"))
if (require(ggplot2)) {
autoplot(cib)
autoplot(cib, parm = c("hp", "disp"))
}
#' working-hotelling-adjusted intervals
(ciwh <- confint_adjust(fit, method = "wh"))