1d:T757,# Wrapper to compute confidence intervals from glms Computes confidence intervals from the output of a glm, by calling to glht(multcomp). ```r CIGLM(x, conf.level = 0.95, method = c("Raw", "Adj", "Bonf")) ``` ## Arguments - `x`: a object of class `"glm"`, `"gamlss"`, or `"glm.nb"` as can be obtained by calling to function `glm`, function `gamlss` in package `gamlss`, or function `glm.nb` in package `MASS` - `conf.level`: confidence level, a single numeric value between 0.5 and 1 - `method`: a single character string, with `"Raw"` for unadjusted intervals, `"Adj"` for multiplicity adjusted intervals taking the correlations into account, or `"Bonf"` for a Bonferroni adjustment ## Details This is just a wrapper to `confint.glht` of package `multcomp`. Note that except for the simple general linear model with assumption of Gaussian response, the resulting intervals are exact intervals. In other cases, the methods are only asymptotically correct, hence might give misleading results for small sample sizes! ## Returns An object of class `"confint.glht"` ## See Also `confint.glht` in package `multcomp` for the function that is used internally, `UnlogCI` for a simple function to bring confidence intervals back to the original scales when there is a log or logit link, with appropriate naming. ## Examples ```r data(Diptera) library(multcomp) modelfit <- glm(Ges ~ Treatment, data=Diptera, family=quasipoisson) comps <- glht(modelfit, mcp(Treatment="Tukey")) CIs<-CIGLM(comps, method="Raw") CIs CIsAdj<-CIGLM(comps, method="Adj") CIsAdj CIsBonf<-CIGLM(comps, method="Bonf") CIsBonf library(gamlss) modelfit2 <- gamlss(Ges ~ Treatment, data=Diptera, family=NBI) comps2 <- glht(modelfit2, mcp(Treatment="Tukey")) CIs2<-CIGLM(comps2, method="Raw") CIs2 CIsAdj2<-CIGLM(comps2, method="Adj") CIsAdj2 CIsBonf2<-CIGLM(comps2, method="Bonf") CIsBonf2 ```

CIGLM function