gmodels (version 2.18.1)

# 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 `mer` objects are provided.

## Usage

```ci(x, confidence=0.95, alpha=1 - confidence, ...)
# S3 method for numeric
ci(x, confidence=0.95, alpha=1-confidence, na.rm=FALSE, ...)
# S3 method for binom
ci(x, confidence=0.95, alpha=1-confidence, ...)
# S3 method for lm
ci(x, confidence=0.95, alpha=1-confidence, ...)
# S3 method for lme
ci(x, confidence=0.95, alpha=1-confidence, ...)

# S3 method for estimable
ci(x, confidence=0.95, alpha=1-confidence, ...)
# S3 method for 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`.

`confint`, `lm`, `summary.lm`

## Examples

```# NOT RUN {
# 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)

# }
# NOT RUN {
<!-- %\dontrun{ -->
# }
# NOT RUN {
<!-- %# mer example -->
# }
# NOT RUN {
<!-- %library(lme4) -->
# }
# NOT RUN {
<!-- %fm2 &lt;- lmer(Reaction ~ Days + (1|Subject) + (0+Days|Subject), sleepstudy) -->
# }
# NOT RUN {
<!-- %ci(fm2) -->
# }
# NOT RUN {
<!-- %} -->
# }
# NOT RUN {

# }
```