gmodels (version 2.11.0)

ci: 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 lmer objects are provided.

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.

synopsis

ci(x, confidence = 0.95, alpha = 1 - confidence,...) ## S3 method for class 'default': 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,...)

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)