ci: Compute Confidence Intervals

In gmodels: Various R Programming Tools for Model Fitting

Compute Confidence Intervals

Description

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.

Usage

  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, ...)

Arguments

x	object from which to compute confidence intervals.
confidence	confidence level. Defaults to 0.95.
alpha	type one error rate. Defaults to 1.0-confidence
na.rm	boolean indicating whether missing values should be removed. Defaults to FALSE.
...	Arguments for methods

Value

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.

Author(s)

Gregory R. Warnes [e-mail]

See Also

confint, lm, summary.lm

Examples

# 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)

gmodels documentation built on May 17, 2022, 9:05 a.m.