confint.drc.RdComputes confidence intervals for one or more parameters in a model of class 'drc'.
# S3 method for drc confint(object, parm, level = 0.95, pool = TRUE, ...)
| object | a model object of class 'drc'. |
|---|---|
| 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. |
| pool | logical. If TRUE curves are pooled. Otherwise they are not. This argument only works for models with
independently fitted curves as specified in |
| … | additional argument(s) for methods. Not used. |
For binomial and Poisson data the confidence intervals are based on the normal distribution, whereas t distributions are used of for continuous/quantitative data.
A matrix (or vector) with columns giving lower and upper confidence limits for each parameter. These will be labelled as (1-level)/2 and 1 - (1-level)/2 in
## Fitting a four-parameter log-logistic model ryegrass.m1 <- drm(rootl ~ conc, data = ryegrass, fct = LL.4()) ## Confidence intervals for all parameters confint(ryegrass.m1)#> 2.5 % 97.5 % #> b:(Intercept) 2.01211606 3.9523221 #> c:(Intercept) 0.03878752 0.9240389 #> d:(Intercept) 7.39961398 8.1863026 #> e:(Intercept) 2.67052621 3.4453837## Confidence interval for a single parameter confint(ryegrass.m1, "e")#> 2.5 % 97.5 % #> e:(Intercept) 2.670526 3.445384