glmlist: Create a Model List Object
In vcdExtra: 'vcd' Extensions and Additions

Description Usage Arguments Details Value Author(s) See Also Examples

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.

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

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

`...`	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

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.

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

Michael Friendly; coef method by John Fox

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.

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")

Loading required package: vcd
Loading required package: grid
Loading required package: gnm
[1] "indep"  "coleff" "roweff" "linlin"
[1] "Indep"   "Col"     "Row"     "LinxLin"
Likelihood summary table:
           AIC    BIC LR Chisq Df Pr(>Chisq)    
Indep   209.59 220.19   47.418 15  3.155e-05 ***
Col     179.00 195.50    6.829 10     0.7415    
Row     174.45 188.59    6.281 12     0.9013    
LinxLin 174.07 185.85    9.895 14     0.7698    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
                            Indep        Col        Row     LinxLin
(Intercept)            4.18756842  4.8631072  4.7061332  3.37942319
mental.L               0.04507501  0.6795332 -0.6818052 -0.66051890
mental.Q              -0.30073728 -0.3233129 -0.3277282 -0.32176183
mental.C               0.39412292  0.3936983  0.1992104  0.39415885
ses.L                 -0.04968094 -1.0342736  0.5629992 -0.99933120
ses.Q                 -0.30335318 -0.5581022 -0.3328887 -0.33029582
ses.C                 -0.19797985 -0.1707521 -0.1979530 -0.19811915
ses^4                  0.17490822  0.1230409  0.1749295  0.17494245
ses^5                  0.14682648  0.2429662  0.1468266  0.14682693
ses1:Rscore                    NA -0.4459213         NA          NA
ses2:Rscore                    NA -0.4594090         NA          NA
ses3:Rscore                    NA -0.3342208         NA          NA
ses4:Rscore                    NA -0.2814884         NA          NA
ses5:Rscore                    NA -0.1393421         NA          NA
ses6:Rscore                    NA         NA         NA          NA
mentalWell:Cscore              NA         NA -0.3068185          NA
mentalMild:Cscore              NA         NA -0.1617300          NA
mentalModerate:Cscore          NA         NA -0.1433864          NA
mentalImpaired:Cscore          NA         NA         NA          NA
Rscore:Cscore                  NA         NA         NA  0.09068661
    Indep       Col       Row   LinxLin 
47.417847  6.829334  6.280761  9.895124