ci {gmodels} | R Documentation |
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.
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 |
sim.lmer |
Logical value. If TRUE confidence
intervals will be estimated using \Link[Matrix]{mcmcsamp} . This option only takes effect for lmer
objects. |
n.sim |
Number of samples to take in \Link[Matrix]{mcmcsamp} . |
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 Gregory_R_Warnes@groton.pfizer.com
# 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)