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glm
s
in the poission family), where it is desired to find the
highest-order terms necessary to achieve a satisfactory fit.
Using anova
on the resulting glmlist
object will then give sequential tests of the pooled contributions of
all terms of degree $k+1$ over and above those of degree $k$.
This function is also intended as an example of a generating function
for glmlist
objects, to facilitate model comparison, extraction,
summary and plotting of model components, etc., perhaps using lapply
or similar.Kway(formula, family=poisson, data, ..., order = nt, prefix = "kway")
+
signs.
as.data.frame
to a data frame) containing the variables in the model. If not
found in data, the variables areglm
glmlist
object.glmlist
, of length order+1
containing the 0-way, 1-way, ...
models up to degree order
.y
as the response in the formula
, the 0-way (null) model
is y ~ 1
.
The 1-way ("main effects") model is that specified in the
formula
argument. The k-way model is generated using the formula
. ~ .^k
.
With the default order = nt
, the final model is the saturated model.
As presently written, the function requires a two-sided formula with an explicit
response on the LHS. For frequency data in table form (e.g., produced by xtabs
)
you the data
argument is coerced to a data.frame, so you
should supply the formula
in the form Freq ~
....glmlist
,
summarise
## artificial data
factors <- expand.grid(A=factor(1:3), B=factor(1:2), C=factor(1:3), D=factor(1:2))
Freq <- rpois(nrow(factors), lambda=40)
df <- cbind(factors, Freq)
mods3 <- Kway(Freq ~ A + B + C, data=df, family=poisson)
summarise(mods3)
mods4 <- Kway(Freq ~ A + B + C + D, data=df, family=poisson)
summarise(mods4)
# JobSatisfaction data
data(JobSatisfaction, package="vcd")
modSat <- Kway(Freq ~ management+supervisor+own, data=JobSatisfaction, family=poisson, prefix="JSat")
summarise(modSat)
anova(modSat, test="Chisq")
# Rochdale data: very sparse, in table form
data(Rochdale, package="vcd")
modRoch <- Kway(Freq~EconActive + Age + HusbandEmployed + Child + Education + HusbandEducation + Asian + HouseholdWorking,
data=Rochdale, family=poisson)
summarise(modRoch)
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