estimate_contrast {glmglrt} | R Documentation |
Point estimates of contrasts
Description
This S3 generic function allows the computation of point estimates of contrasts
(i.e. linear combinations) of fixed-effects in many models
The default implementation computes Wald's confidence intervals with any model as long as it implements fixcoef
, returning a vector of fixed effects.
Usage
estimate_contrast(model, contrast, method = NULL, ...)
## Default S3 method:
estimate_contrast(model, contrast, method = NULL, ...)
Arguments
model |
a fitted statistical model such as a glm or a coxph. |
contrast |
numeric vector of the same length as the number of coefficients in the model; it describes the contrast |
method |
character string value; specification of the algorithm used (implementation dependent). NULL must be accepted. Suggested values are "ML" for maximum-likelihood, "REML" for restricted maximum-likelihood and "OLS" for ordinary least squares. |
... |
Additional parameters that may be used by some implementations. |
Details
This function should consistent with confint_contrast
and p_value_contrast
as they are designed to be used together.
If a null hypothesis (H0) is specified, it MUST be ignored by estimate_contrast
.
If you want to make it consistent with p_value_contrast you may substract H0 from the output of estimate_contrast
and confint_contrast
.
Value
A single numeric value (vector of length 1) equal to the point estimate of the contrast, with the name "pvalue".
Methods (by class)
-
default
: Compute contrasts of fixed-effects in any model implementingfixcoef
. It basically computessum(fixcoef(model) * contrast)
.
See Also
Other Contrast functions:
confint_contrast()
,
estimate_confint_contrast()
,
p_value_contrast()
Examples
data(mtcars)
model1 = glm(family="gaussian", data=mtcars, hp ~ 0+factor(gear))
# do cars with 5 gears have more horse power (hp) than cars with 4 gears ?
estimate_contrast(model1, c(0,-1,1))
# now, we fit an equivalent model (same distribution and same predictions)
model2 = glm(family=gaussian(log), data=mtcars, hp ~ 0+factor(gear))
# do cars with 5 gears have at least twice the horse power than cars with 4 gears ?
estimate_contrast(model1, c(0,-1,0.5))