glmlist {vcdExtra}

Create a Model List Object

Description

glmlist creates a glmlist object containing a list of fitted glm objects with their names. loglmlist does the same for loglm objects.

The intention is to provide object classes to facilitate model comparison, extraction, summary and plotting of model components, etc., perhaps using lapply or similar.

There exists a anova.glm method for glmlist objects. Here, a coef method is also defined, collecting the coefficients from all models in a single object of type determined by result.

Usage

glmlist(...)
loglmlist(...)

## S3 method for class 'glmlist'
coef(object, result=c("list", "matrix", "data.frame"), ...)

Arguments

...

One or more model objects, as appropriate to the function, optionally assigned names as in list.

object

a glmlist object

result

type of the result to be returned

Details

The arguments to glmlist or loglmlist are of the form value or name=value.

Any objects which do not inherit the appropriate class glm or loglm are excluded, with a warning.

In the coef method, coefficients from the different models are matched by name in the list of unique names across all models.

Value

An object of class glmlist loglmlist, just like a list, except that each model is given a name attribute.

Author(s)

Michael Friendly; coef method by John Fox

See Also

The function llist in package Hmisc is similar, but perplexingly more general.

The function anova.glm also handles glmlist objects

LRstats gives LR statistics and tests for a glmlist object.

Examples

data(Mental)
indep <- glm(Freq ~ mental+ses,
                family = poisson, data = Mental)
Cscore <- as.numeric(Mental$ses)
Rscore <- as.numeric(Mental$mental)

coleff <- glm(Freq ~ mental + ses + Rscore:ses,
                family = poisson, data = Mental)
roweff <- glm(Freq ~ mental + ses + mental:Cscore,
                family = poisson, data = Mental)
linlin <- glm(Freq ~ mental + ses + Rscore:Cscore,
                family = poisson, data = Mental)
                
# use object names
mods <- glmlist(indep, coleff, roweff, linlin)
names(mods)

# assign new names
mods <- glmlist(Indep=indep, Col=coleff, Row=roweff, LinxLin=linlin)
names(mods)

LRstats(mods)

coef(mods, result='data.frame')

#extract model components
unlist(lapply(mods, deviance))

res <- lapply(mods, residuals)
boxplot(as.data.frame(res), main="Residuals from various models")