R: Compute Confidence Intervals

ci {gmodels} | R Documentation

## 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 greg@warnes.net

### 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)

[Package gmodels version 2.18.1 Index]