Compute Confidence Intervals
Compute and display confidence intervals for model
estimates. Methods are provided for the mean of a numeric vector
ci.default, the probability of a binomial vector
ci.binom, and for lm, lme, and mer objects are
provided.
ci(x, confidence=0.95, alpha=1 - confidence, ...) ## S3 method for class 'numeric' ci(x, confidence=0.95, alpha=1-confidence, na.rm=FALSE, ...) ## S3 method for class 'binom' ci(x, confidence=0.95, alpha=1-confidence, ...) ## S3 method for class 'lm' ci(x, confidence=0.95, alpha=1-confidence, ...) ## S3 method for class 'lme' ci(x, confidence=0.95, alpha=1-confidence, ...) ## S3 method for class 'estimable' ci(x, confidence=0.95, alpha=1-confidence, ...) ## S3 method for class 'fit_contrast' ci(x, confidence=0.95, alpha=1-confidence, ...)
x |
object from which to compute confidence intervals. |
confidence |
confidence level. Defaults to 0.95. |
alpha |
type one error rate. Defaults to 1.0- |
na.rm |
boolean indicating whether missing values should be
removed. Defaults to |
... |
Arguments for methods |
vector or matrix with one row per model parameter and elements/columns
Estimate, CI lower, CI upper, Std. Error,
DF (for lme objects only), and p-value.
Gregory R. Warnes greg@warnes.net
# mean and confidence interval ci( rnorm(10) ) # binomial proportion and exact confidence interval b <- rbinom( prob=0.75, size=1, n=20 ) ci.binom(b) # direct call class(b) <- 'binom' ci(b) # indirect call # confidence intervals for regression parameteres data(state) reg <- lm(Area ~ Population, data=as.data.frame(state.x77)) ci(reg)
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