Computes approximate standard errors for (a selection of) individual
parameters or one or more linear combinations of the parameters in a
gnm
(generalized nonlinear model) object. By default, a
check is made first on the estimability of each specified combination.
1 2 
model 
a model object of class 
estimate 
(optional) specifies parameters or linear
combinations of parameters for which to find standard errors. In the
first case either a character vector of names, a
numeric vector of indices or 
checkEstimability 
logical: should the estimability of all specified combinations be checked? 
Vcov 
either NULL, or a matrix 
dispersion 
either NULL, or a positive number 
... 
possible further arguments for

A data frame with two columns:
Estimate 
The estimated parameter combinations 
Std. Error 
Their estimated standard errors 
If available, the column names of coefMatrix
will be used to name
the rows.
In the case where estimate
is a numeric vector, se
will
assume that indices have been specified if all the values of
estimate
are in seq(length(coef(model))
.
Where both Vcov
and dispersion
are supplied, the
variancecovariance matrix of estimated model coefficients is taken to
be Vcov * dispersion
.
David Firth and Heather Turner
gnm
, getContrasts
,
checkEstimable
, ofInterest
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17  set.seed(1)
## Fit the "UNIDIFF" mobility model across education levels
unidiff < gnm(Freq ~ educ*orig + educ*dest +
Mult(Exp(educ), orig:dest),
ofInterest = "[.]educ", family = poisson,
data = yaish, subset = (dest != 7))
## Deviance is 200.3
## Get estimate and se for the contrast between educ4 and educ5 in the
## UNIDIFF multiplier
mycontrast < numeric(length(coef(unidiff)))
mycontrast[ofInterest(unidiff)[4:5]] < c(1, 1)
se(unidiff, mycontrast)
## Get all of the contrasts with educ5 in the UNIDIFF multipliers
getContrasts(unidiff, rev(ofInterest(unidiff)))

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