Fitting Additive Binomial Regression Models
Description
Workhorse function for addreg
with
binomial
family.
Usage
1 
Arguments
y 
binomial response. May be a single column of 0/1 or two columns, giving the number of successes and failures. 
x 
nonnegative design matrix. Must have an intercept column. 
start 
starting values for the parameters in the linear predictor. 
control 
list of parameters for controlling the
fitting process, passed to

allref 
a list of all parameterisations for this
model, obtained from 
Details
An additive binomial fit can be converted into an additive
Poisson fit via the multinomial–Poisson transformation
(Baker, 1994). This function transforms the data as
described by Donoghoe and Marschner (2014) and passes it to addreg
with a Poisson family to get the maximum likelihood
estimate. The coefficients (and other values) from the
Poisson model are transformed back to relate to the
additive binomial model.
This is a workhorse function for addreg
when
a binomial
family is specified. It would not usually
be called directly.
Value
A list of (most of) the components needed for an object of
class "addreg"
; see addreg
for
details.
Author(s)
Mark W. Donoghoe Mark.Donoghoe@mq.edu.au
References
Baker, S. G. (1994). The multinomial–Poisson transformation. The Statistician 43(4): 495–504.
Donoghoe, M. W. and I. C. Marschner (2014). Stable computational methods for additive binomial models with application to adjusted risk differences. Computational Statistics and Data Analysis 80: 184–196.
See Also
addreg