Sets constraints on specified item parameters in Bayesian analysis of roll call data by generating appropriate priors and start values for Markov chain Monte Carlo iterations.
constrain.items(obj, dropList = list(codes = "notInLegis", lop = 0),
x, d = 1)
a list with elements:
prior means for ideal points. A matrix of dimensions number
of legislators in obj
by d
.
prior meansprecisions for ideal points. A matrix of dimensions number
of legislators in obj
by d
.
prior means for item parameters. A matrix of dimensions number
of items or votes in obj
by d+1
.
prior meansprecisions for item parameters. A matrix of dimensions number
of items or votes in obj
by d+1
.
start values for ideal points. A matrix of dimensions number
of legislators in obj
by d
.
start values for ideal points. A matrix of dimensions number
of items or votes in obj
by d+1
.
an object of class rollcall
.
a list
(or alist
)
indicating which voting decisions, legislators and/or roll calls are
to be excluded from the subsequent analysis; see
dropRollCall
for details.
a list
containing elements with names matching
votes found in dimnames(object$votes)[[2]]
(but after any
subsetting specified by dropList
). Each component of the
list must be a vector containing d
elements, specifying the
value to which the item discrimination parameters should be
constrained, in each of the d
dimensions. The intercept or
item difficultly parameter will not be constrained.
numeric, positive integer, the number of dimensions for which to set up the priors and start values.
constrain.items
and its cousin,
constrain.legis
are usefully thought of as
“pre-processor” functions, generating priors and start
values for both the item parameters and the ideal points. For the
items specified in x
, the prior mean for each dimension is set
to the value given in x
, and the prior precision for each
dimension is set to 1e12
(i.e., a near-degenerate
“spike” prior). For the other items, the priors are set to a
mean of 0 and precision 0.01. All of the ideal points are given
normal priors with mean 0, precision 1.
Start values are also generated for both ideal points and item
parameters. The start values for the items specified in x
are
set to the values specified in x
. The list resulting from
constrain.items
can then be given as the value for the
parameters priors
and startvals
when ideal
is run. The user is responsible for ensuring that a sufficient number
of items are constrained such that when ideal
is run,
the model parameters are identified.
dropRollCall
is first called to generate the desired
roll call matrix. The entries of the roll call matrix are mapped to
c(0,1,NA)
using the codes
component of the
rollcall
object
. See the discussion in the
documentation of ideal
for details on the generation of
start values.
rollcall
, ideal
,
constrain.legis